WO2007136897A1 - Estimating the location of a wireless terminal based on assisted gps and pattern matching - Google Patents

Estimating the location of a wireless terminal based on assisted gps and pattern matching Download PDF

Info

Publication number
WO2007136897A1
WO2007136897A1 PCT/US2007/062010 US2007062010W WO2007136897A1 WO 2007136897 A1 WO2007136897 A1 WO 2007136897A1 US 2007062010 W US2007062010 W US 2007062010W WO 2007136897 A1 WO2007136897 A1 WO 2007136897A1
Authority
WO
WIPO (PCT)
Prior art keywords
wireless terminal
location
estimate
satellite signal
terminal based
Prior art date
Application number
PCT/US2007/062010
Other languages
French (fr)
Inventor
Tarun Kumar Bhattachaya
Original Assignee
Polaris Wireless, Inc.
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Polaris Wireless, Inc. filed Critical Polaris Wireless, Inc.
Priority to EP07756889A priority Critical patent/EP2027483A1/en
Publication of WO2007136897A1 publication Critical patent/WO2007136897A1/en

Links

Classifications

    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04WWIRELESS COMMUNICATION NETWORKS
    • H04W64/00Locating users or terminals or network equipment for network management purposes, e.g. mobility management
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01SRADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S19/00Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
    • G01S19/01Satellite radio beacon positioning systems transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
    • G01S19/03Cooperating elements; Interaction or communication between different cooperating elements or between cooperating elements and receivers
    • G01S19/05Cooperating elements; Interaction or communication between different cooperating elements or between cooperating elements and receivers providing aiding data
    • G01S19/06Cooperating elements; Interaction or communication between different cooperating elements or between cooperating elements and receivers providing aiding data employing an initial estimate of the location of the receiver as aiding data or in generating aiding data
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01SRADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S19/00Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
    • G01S19/01Satellite radio beacon positioning systems transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
    • G01S19/13Receivers
    • G01S19/24Acquisition or tracking or demodulation of signals transmitted by the system
    • G01S19/25Acquisition or tracking or demodulation of signals transmitted by the system involving aiding data received from a cooperating element, e.g. assisted GPS
    • G01S19/252Employing an initial estimate of location in generating assistance data
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01SRADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S5/00Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations
    • G01S5/02Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations using radio waves
    • G01S5/0205Details
    • G01S5/021Calibration, monitoring or correction
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01SRADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S19/00Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
    • G01S19/01Satellite radio beacon positioning systems transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
    • G01S19/13Receivers
    • G01S19/14Receivers specially adapted for specific applications
    • G01S19/17Emergency applications
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04WWIRELESS COMMUNICATION NETWORKS
    • H04W84/00Network topologies
    • H04W84/02Hierarchically pre-organised networks, e.g. paging networks, cellular networks, WLAN [Wireless Local Area Network] or WLL [Wireless Local Loop]
    • H04W84/04Large scale networks; Deep hierarchical networks
    • H04W84/06Airborne or Satellite Networks

Definitions

  • the present invention relates to telecommunications in general, and, more particularly, to a technique for estimating the location of a wireless terminal and using the estimate of the location in a location-based application.
  • FIG. 1 depicts a diagram of the salient components of wireless telecommunications system 100 in accordance with the prior art.
  • Wireless telecommunications system 100 comprises: wireless terminal 101, base stations 102-1, 102-2, and 102-3, wireless switching center 111, assistance server 112, location client 113, and Global Positioning System ("GPS") constellation 121.
  • Wireless telecommunications system 100 provides wireless telecommunications service to all of geographic region 120, in well-known fashion.
  • the salient advantage of wireless telecommunications over wireline telecommunications is the mobility that is afforded to the users.
  • the salient disadvantage of wireless telecommunications lies in that fact that because the user is mobile, an interested party might not be able to readily ascertain the location of the user.
  • Such interested parties might include both the user of the wireless terminal and remote parties. There are a variety of reasons why the user of a wireless terminal might be interested in knowing his or her location. For example, the user might be interested in telling a remote party where he or she is or might seek advice in navigation.
  • a remote party might be interested in knowing the location of the user.
  • the recipient of an E 9-1-1 emergency call from a wireless terminal might be interested in knowing the location of the wireless terminal so that emergency services vehicles can be dispatched to that location.
  • the location of a wireless terminal is estimated to be at the center of the cell or centroid of the sector in which the wireless terminal is located.
  • This technique is advantageous in that it does not require that additional hardware be added to the wireless terminal or to the wireless telecommunications system, and, therefore, the first technique can be inexpensively implemented in legacy systems.
  • the first technique is only accurate (in present cellular systems), however, to within a few kilometers, and, therefore, it is generally not acceptable for applications (e.g., emergency services dispatch, etc.) that require higher accuracy.
  • the location of a wireless terminal is estimated by triangulating the angle of arrival or multilaterating the time of arrival of the signals transmitted by the wireless terminal.
  • This technique can achieve accuracy to within a few hundreds of meters and is advantageous in that it can be used with legacy wireless terminals.
  • the disadvantage of this second technique is that it generally requires that hardware be added to the telecommunication system's base stations, which can be prohibitively expensive.
  • the location of a wireless terminal is estimated by a radio navigation unit, such as, for example, a Global Positioning System (GPS) receiver, that is incorporated into the wireless terminal.
  • GPS Global Positioning System
  • This technique is typically accurate to within tens of meters but is disadvantageous in that it does not work consistently well indoors, in heavily wooded forests, or in urban canyons. Furthermore, the accuracy of this third technique can be severely degraded by multipath reflections.
  • the present invention enables the construction and use of a system that can estimate the location of a wireless terminal without some of the costs and limitations associated with techniques for doing so in the prior art.
  • the present invention is based on the recognition that there are traits of electromagnetic signals that are dependent on topography, the receiver, the location of the transmitter, and other factors. For example, if a particular radio station is known to be received strongly at a first location and weakly at a second location, and a given wireless terminal at an unknown location is receiving the radio station weakly, it is more likely that the wireless terminal is at the second location than at the first location. [0013] By quantifying "strongly” and “weakly” and extending this principle to multiple traits and multiple signals, the present invention can estimate the location of a wireless terminal with greater accuracy.
  • the illustrative embodiment comprises: generating a first non-GPS-derived estimate of the location of a wireless terminal based on a first measurement of a trait of a first signal; and generating assistance data for a satellite signal that is received by the wireless terminal, wherein the assistance data is based on the first non-GPS-derived estimate of the location of the wireless terminal.
  • Figure 1 depicts a map of a portion of a wireless telecommunications system in the prior art.
  • Figure 2 depicts a diagram of the salient components of wireless telecommunications system 200 in accordance with the illustrative embodiment of the present invention.
  • Figure 3 depicts a block diagram of the salient components of location server 214, as shown in Figure 2, in accordance with the illustrative embodiment.
  • Figure 4 depicts a flowchart of the salient processes performed in accordance with the illustrative embodiment of the present invention.
  • Figure 5 depicts a flowchart of the salient processes performed in accordance with process 401 of Figure 4: building Location-Trait Database 313.
  • Figures 6a through 6k depict geographic regions and their deconstruction into a plurality of locations.
  • Figure 6L depicts an alternative partitioning of geographic region 220 into 64 square locations.
  • Figure 6m depicts a graphical representation of an adjacency graph of geographic region 220 as partitioned in Figures 6c through 6e.
  • Figure 6n depicts a graphical representation of an adjacency graph of the highway intersection partitioned in Figures 6h through 6k.
  • Figure 7 depicts a flowchart of the salient processes performed as part of process 402 of Figure 4: populating Trait-Correction Database 313.
  • Figures 8a through 8c depict illustrative distortion and correction curves.
  • Figure 9 depicts a flowchart of the salient processes performed in process 403 (of Figure 4): maintaining Location-Trait Database 313.
  • Figure 10 depicts a flowchart of the salient processes performed in process 701 of Figure 7: estimating the location of wireless terminal 201.
  • Figure lla depicts a flowchart of the salient processes performed in process 901 of Figure 9: generating the probability distribution for the location of wireless terminal 201 based on the traits of one or more signals received by, or transmitted to, wireless terminal 201 at instants H 1 through H ⁇ .
  • Figure lib depicts a flowchart of the salient processes performed in accordance with process 1104 of Figure lla: search area reduction.
  • Figure lie depicts a flowchart of the salient processes performed in accordance with process 1105: generating the probability distribution for that wireless terminal 201 at each of instants H 1 through H ⁇ .
  • Figure 12 depicts a flowchart of the salient processes performed in process 902 of Figure 9: generating the probability distribution for the location of wireless terminal 201 based on GPS-derived information (i.e., information from GPS constellation 221).
  • GPS-derived information i.e., information from GPS constellation 221).
  • Figure 13 depicts a flowchart of the salient processes performed in process 903 of Figure 9: combining non-GPS-based and GPS-based probability distributions for the location of wireless terminal 201.
  • Figure 14 depicts a first example of combining non-GPS-based instants H 1 through /Vy and GPS-based instants Gi through G z into composite instants J 1 through J f .
  • Figure 15 depicts a second example of combining non-GPS-based instants H 1 through Hy and GPS-based instants G 1 through Gz into composite instants J 1 through JF-
  • location is defined as a one-dimensional point, a two-dimensional area, or a three-dimensional volume.
  • staying probability is defined as an estimate of the probability Ps(b, T, N, W) that wireless terminal W in location b at calendrical time T will still be in location b at time T+ ⁇ t, given environmental conditions, N.
  • moving probability is defined as an estimate of the probability P/vib, T, N, W, c) that wireless terminal W in location b at calendrical time T will be in adjacent location c at time T+ ⁇ t, given environmental conditions, N.
  • environment conditions N are defined to include one or more physical aspects of the environment, and includes, but is not limited to, the weather, the astronomical conditions, atmospheric conditions, the quantity and density of radio traffic, the quantity and density of vehicular traffic, road and sidewalk construction, etc.
  • calendrical time T is defined as the time as denominated in one or more measures (e.g., seconds, minutes, hours, time of day, day, day of week, month, month of year, year, etc.).
  • Wireless telecommunications system 200 comprises: wireless terminal 201, base stations 202-1, 202-2, and 202-3, wireless switching center 211, assistance server 212, location client 213, location server 214, and GPS constellation 221, which are interrelated as shown.
  • the illustrative embodiment provides wireless telecommunications service to all of geographic region 220, in well- known fashion, estimates the location of wireless terminal 201 within geographic region 220, and uses that estimate in a location-based application.
  • wireless telecommunications service is provided to wireless terminal 201 in accordance with the Universal Mobile Telecommunications System, which is commonly known as "UMTS.”
  • UMTS Universal Mobile Telecommunications System
  • GSM Global System Mobile
  • CDMA-2000 Code Division Multiple Access
  • IS-136 TDMA Time Division Multiple Access
  • IS-95 Code Division Multiple Access
  • 3G Wideband CDMA Code Division Multiple Access
  • IEEE 802.11 WiFi WiMax
  • Bluetooth etc.
  • Wireless terminal 201 comprises the hardware and software necessary to be UMTS-compliant and to perform the processes described below and in the accompanying figures.
  • wireless terminal 201 is capable of: i. measuring one or more traits of one of more electromagnetic signals and of reporting the measurements to location server 214, and ii. transmitting one or more signals and of reporting the transmission parameters of the signals to location server 214, and iii. receiving GPS assistance data from assistance server 212 to assist it in acquiring and processing GPS ranging signals.
  • Wireless terminal 201 is mobile and can be at any location within geographic region 220. Although wireless telecommunications system 200 comprises only one wireless terminal, it will be clear to those skilled in the art, after reading this disclosure, how to make and use alternative embodiments of the present invention that comprise any number of wireless terminals.
  • Base stations 202-1, 202-2, and 202-3 communicate with wireless switching center 211 and with wireless terminal 201 via radio in well-known fashion.
  • base stations are also commonly referred to by a variety of alternative names such as access points, nodes, network interfaces, etc.
  • access points nodes
  • network interfaces etc.
  • the illustrative embodiment comprises three base stations, it will be clear to those skilled in the art, after reading this disclosure, how to make and use alternative embodiments of the present invention that comprise any number of base stations.
  • base stations 202-1, 202-2, and 202-3 are terrestrial, immobile, and within geographic region 220. It will be clear to those skilled in the art, after reading this disclosure, how to make and use alternative embodiments of the present invention in which some or all of the base stations are airborne, marine-based, or space-based, regardless of whether or not they are moving relative to the Earth's surface, and regardless of whether or not they are within geographic region 220.
  • Wireless switching center 211 comprises a switch that orchestrates the provisioning of telecommunications service to wireless terminal 201 and the flow of information to and from location server 214, as described below and in the accompanying figures.
  • wireless switching centers are also commonly referred to by other names such as mobile switching centers, mobile telephone switching offices, routers, etc.
  • the illustrative embodiment comprises one wireless switching center
  • the wireless switching centers can exchange and share information that is useful in estimating the location of the wireless terminal.
  • the wireless switching centers can use the IS-41 protocol messages Handof fMeasurementRequest and Handof fMeasurementRequest2 to elicit signal-strength measurements from one another.
  • the use of two or more wireless switching centers is particularly common when the geographic area serviced by the wireless switching center is small (e.g., local area networks, etc.) or when multiple wireless switching centers serve a common area.
  • all of the base stations servicing wireless terminal 201 are associated with wireless switching center 211. It will be clear to those skilled in the art, after reading this disclosure, how to make and use alternative embodiments of the present invention in which any number of base stations are associated with any number of wireless switching centers.
  • Assistance server 212 comprises hardware and software that is capable of performing the processes described below and in the accompanying figures.
  • assistance server 212 generates GPS assistance data for wireless terminal 201 to aid wireless terminal 201 in acquiring and processing GPS ranging signals from GPS constellation 221.
  • assistance server 212 is a separate physical entity from location server 214; however, it will be clear to those skilled in the art, after reading this disclosure, how to make and use alternative embodiments of the present invention in which assistance server 212 and location server 214 share hardware, software, or both.
  • Location client 213 comprises hardware and software that use the estimate of the location of wireless terminal 201 - provided by location server 214 - in a location-based application, as described below and in the accompanying figures.
  • Location server 214 comprises hardware and software that generate one or more estimates of the location of wireless terminal 201 as described below and in the accompanying figures. It will be clear to those skilled in the art, after reading this disclosure, how to make and use location server 214. Furthermore, although location server 214 is depicted in Figure 2 as physically distinct from wireless switching center 211, it will be clear to those skilled in the art, after reading this disclosure, how to make and use alternative embodiments of the present invention in which location server 214 is wholly or partially integrated with wireless switching center 211.
  • location server 214 communicates with wireless switching center 211, assistance server 212, and location client 213 via a local area network; however it will be clear to those skilled in the art, after reading this disclosure, how to make and use alternative embodiments of the present invention in which location server 214 communicates with one or more of these entities via a different network such as, for example, the Internet, the Public Switched Telephone Network (PSTN), etc.
  • PSTN Public Switched Telephone Network
  • wireless switching center 211, assistance server 212, location client 213, and location server 214 are outside of geographic region 220. It will be clear to those skilled in the art, after reading this disclosure, how to make and use alternative embodiments of the present invention in which some or all of wireless switching center 211, assistance server 212, location client 213, and location server 214 are instead within geographic region 220.
  • Location Server 214 - Figure 3 depicts a block diagram of the salient components of location server 214 in accordance with the illustrative embodiment.
  • Location server 214 comprises: processor 301, memory 302, and local-area network transceiver 303, which are interconnected as shown.
  • Processor 301 is a general-purpose processor that is capable of executing operating system 311 and application software 312, and of populating, amending, using, and managing Location-Trait Database 313 and Trait-Correction Database 314, as described in detail below and in the accompanying figures. It will be clear to those skilled in the art how to make and use processor 301.
  • Memory 302 is a non-volatile memory that stores: i. operating system 311, and ii. application software 312, and iii. Location-Trait Database 313, and iv. Trait-Correction Database 314. It will be clear to those skilled in the art how to make and use memory 302.
  • Transceiver 303 enables location server 214 to transmit and receive information to and from wireless switching center 211, assistance server 212, and location client 213. In addition, transceiver 303 enables location server 214 to transmit information to and receive information from wireless terminal 201 and base stations 202-1 through 202-3 via wireless switching center 211. It will be clear to those skilled in the art how to make and use transceiver 303.
  • Operation of the Illustrative Embodiment - Figure 4 depicts a flowchart of the salient processes performed in accordance with the illustrative embodiment of the present invention.
  • Location-Trait Database 313 is built.
  • the "Location-Trait Database” is defined as a database that maps each of a plurality of locations to one or more expected traits associated with a wireless terminal at that location. The details of building Location-Trait Database 313 are described below and in the accompanying figures.
  • Trait-Correction Database 314 is built.
  • the "Trait-Correction Database” is defined as a database that indicates how the measurement of traits can be adjusted to compensate for systemic measurement errors. The details of building Trait-Correction Database 314 are described below and in the accompanying figures.
  • the location of wireless terminal 201 is estimated based on location-trait database 401, trait-correction database 402, and a variety of traits that vary based on the location of wireless terminal 201. The details of process 403 are described below and in the accompanying figures.
  • the estimate of the location of wireless terminal 201 is used in a location-based application, such as and without limitation, E 9- 1-1 service.
  • a location-based application such as and without limitation, E 9- 1-1 service.
  • Process 405 is advantageous because the effectiveness of the illustrative embodiment is based on - and limited by - the accuracy, freshness, and completeness of the contents of Location -Trait Database 313 and Trait-Correction Database 314. The details of process 405 are described below and in the accompanying figures.
  • Building Location-Trait Database 313 - Figure 5 depicts a flowchart of the salient processes performed in accordance with process 401 - building Location- Trait Database 313.
  • geographic region 220 is partitioned into B(T,N) locations, wherein B(T,N) is a positive integer greater than one, and wherein B(T f N) varies as a function of calendrical time T and the environmental conditions N.
  • B(T,N) is a positive integer greater than one
  • B(T f N) varies as a function of calendrical time T and the environmental conditions N.
  • Some traits of the radio frequency spectrum and of individual signals are different at different locations in geographic region 220. Similarly, some traits of the radio frequency spectrum and of individual signals transmitted by wireless terminal 201 change at base stations 202-1, 202-2, and 202-3 when wireless terminal 201 is at different locations. Furthermore, some traits ⁇ e.g., hand -off state, etc.) of wireless telecommunications system 200 change when wireless terminal 201 is at different locations. [0062] When wireless terminal 201 is at a particular location, the values of the traits that vary with the location of wireless terminal 201 represent a "fingerprint" or "signature" for that location that enables location server 214 to estimate the location of wireless terminal 201.
  • wireless terminal 201 For example, suppose that under normal conditions the traits have a first set of values when wireless terminal 201 is at a first location, and a second set of values when wireless terminal 201 is at a second location. Then when wireless terminal 201 is at an unknown location and the traits at that unknown location match the second set of values, it is more likely that wireless terminal 201 is at the second location.
  • Each location is described by: i. a unique identifier b, ii. its dimensionality (e.g., one-dimension, two dimensions, three dimensions, four-dimensions, etc.), iii. the coordinates (e.g., latitude, longitude, altitude, etc.) that define its scope (e.g., position, area, volume, etc.), which can be static or, alternatively, can vary as a function of calendrical time T or the environmental conditions ⁇ /, or both the calendrical time r and the environmental conditions /V. iv.
  • the identifier of each location is an arbitrarily-chosen positive integer. It will be clear to those skilled in the art, after reading this disclosure, how to make and use alternative embodiments of the present invention in which the identifier of some or all locations is not arbitrarily chosen. Furthermore, it will be clear to those skilled in the art, after reading this disclosure, how to make and use alternative embodiments of the present invention in which the identifier of some or all locations is not a positive integer.
  • the scope of each location is three-dimensional and is described by (i) one or more three-dimensional coordinates and geometric identifiers that define its boundaries, (ii) a three-dimensional coordinate that resides at the centroid of the location, and (iii) a description of how the scope changes as a function of calendrical time T and environmental conditions /V. It will be clear to those skilled in the art, after reading this disclosure, how to make and use alternative embodiments of the present invention in which the scope of some or all of the locations are one-dimensional or two-dimensional. Furthermore, it will be clear to those skilled in the art, after reading this disclosure, how to make and use alternative embodiments of the present invention in which the scope of some or all of the locations are not a function of calendrical time T or environmental conditions /V.
  • the scope of two or more locations can overlap at zero, one, two, more than two, or all points of latitude and longitude (e.g., an overpass and underpass, different stories in a multi-story building as described below, etc.).
  • each location are based, at least in part, on: i. natural and man-made physical attributes of geographic region 220 (e.g., buildings, sidewalks, roads, tunnels, bridges, hills, walls, water, cliffs, rivers, etc.), ii. legal laws governing geographic region 220 (e.g., laws that pertain to the location and movement of people and vehicles, etc.), iii. theoretical predictions and empirical data regarding the location and movement of individuals and groups of people and vehicles in geographic region 220, iv. the desired accuracy of the estimates made by location server 214, and v. patterns of the location and movement of people and vehicles within geographic region 220, vi. the calendrical time T 1 and vii. the environmental conditions N, subject to the following considerations:
  • Figure 6a depicts an isometric drawing of geographic region 220 and Figure 6b depicts a map of geographic region 220.
  • Geographic region 220 comprises water fountain 601, park 602, four-story building 603, two-story building 604, various streets, sidewalks, and other features that are partitioned into 28 locations as described below and depicted in Figures 6c through 6e.
  • geographic region 220 comprises approximately four square blocks in the illustrative embodiment, it will be clear to those skilled in the art how to make and use alternative embodiments of the present invention with geographic regions of any size, topology, and complexity.
  • the eight road intersections are partitioned into Locations 1 through 8, as depicted in Figure 6c.
  • the street sections and their adjacent sidewalks up to the edge of buildings 603 and 604 are partitioned into Locations 9 through 19, as depicted in Figure 6d.
  • water fountain 601 is partitioned into Location 20
  • park 602 is partitioned into Location 25
  • each floor of building 604 is classified as one of Locations 21, 22, 23, and 24, and each floor of building 603 is classified as of one of Locations 27 and 28. It will be clear to those skilled in the art, however, after reading this disclosure, how to partition geographic region 220 into any number of locations of any size and shape.
  • a geographic region that comprises a clover-leaf intersection of two, four-lane divided highways is partitioned into 51 locations.
  • Figure 6f depicts an isometric drawing of the intersection
  • Figure 6g depicts a map of the intersection.
  • the grass and medians have been partitioned into 15 locations as depicted in Figure 6g
  • the four ramps have been partitioned into four locations as depicted in Figure 6h
  • the inner or "passing" lanes have been partitioned into eight locations as depicted in Figure 6i
  • the outer or "travel” lanes have been partitioned into eight locations as depicted in Figure 6j.
  • Figure 6L depicts an alternative partitioning of geographic region 220 into 64 square locations.
  • the expected values E(b, 7 " , N, W, Q) for the following traits is associated with each location: i. the expected pathloss of all of the signals receivable by wireless terminal 201 when wireless terminal 201 is at the location, from all transmitters (e.g., base stations 202-1, 202-2, and 202-3, commercial television, commercial radio, navigation, ground-based aviation, etc.), as a function of the calendrical time, T, and the environmental conditions, /V; and ii.
  • Eb/No expected received signal-to-impairment ratio
  • the expected received temporal difference of each pair of multipath components e.g., one temporal difference for one pair of multipath components, a pair of temporal differences for a triplet of multipath components, etc.
  • the expected received temporal difference of each pair of multipath components (e.g., one temporal difference for one pair of multipath components, a pair of temporal differences for a triplet of multipath components, etc.) of all of the signals transmitted by wireless terminal 201 when wireless terminal 201 is in the location as receivable at base stations 202-1, 202-2, and 202-3, as a function of the calendrical time, T, and the environmental conditions, N; and ix.
  • the expected received delay spread (e.g., RMS delay spread, excess delay spread, mean excess delay spread, etc.) of all of the signals receivable by wireless terminal 201 when wireless terminal 201 is in the location, from all transmitters, as a function of the calendrical time, T, and the environmental conditions, /V; and x. the expected received delay spread (e.g., RMS delay spread, excess delay spread, mean excess delay spread, etc.) of all of the signals transmitted by wireless terminal 201 when wireless terminal 201 is in the location as receivable at base stations 202-1, 202-2, and 202-3, as a function of the calendrical time, T 1 and the environmental conditions, /V; and xi.
  • the expected received delay spread e.g., RMS delay spread, excess delay spread, mean excess delay spread, etc.
  • the identities of the neighboring base stations that provide telecommunications service to the location as a function of the calendrical time, T, and the environmental conditions, /V; and xvii. the handover state (e.g., soft, softer, Ix, 2x, etc.) of wireless terminal
  • wireless terminal 201 when wireless terminal 201 is in the location as a function of the calendrical time, T 1 and the environmental conditions, ⁇ /.
  • all signals transmitted by wireless terminal 201 are for communicating with base stations 202-1 through 202-3, and all of the signals received by wireless terminal 201 are:
  • the expected values of these traits are determined through a combination of: i. a plurality of theoretical and empirical radio-frequency propagation models, and ii. a plurality of empirical measurements of the traits within geographic region 220, in well-known fashion.
  • the empirical measurements of the traits are stored within location-trait database 313 and updated as described below.
  • each location b is described by the identities of its adjacent locations, (i.e., the locations that wireless terminal 201 can reasonably move into from location b within one time step ⁇ t.)
  • two locations are considered to be "adjacent" when and only when they have at least two points in common. It will be clear to those skilled in the art, however, after reading this disclosure, how to make and use alternative embodiments of the present invention in which two locations are considered adjacent when they have zero points or one point in common.
  • Adjacency Graph In accordance with the illustrative embodiment, a data structure is created that indicates which locations are adjacent. This data structure is called an "adjacency graph" and it is stored within Location-Trait Database 313 in sparse-matrix format.
  • Figure 6m depicts a graphical representation of the adjacency graph for the 28 locations that compose geographic area 220
  • Figure 6n depicts a graphical representation of the adjacency graph for the 51 locations that compose the highway intersection in Figures 6f through 6k.
  • the adjacency graph is used in the temporal analysis of wireless terminal 201's movements. It will be clear to those skilled in the art, after reading this disclosure, how to make the adjacency graph for any partitioning of geographic region 220.
  • the staying and moving probabilities Ps ⁇ , T 1 . N, W) and PM ⁇ , T, N, W, C) for all b are generated based on a model of the movement of wireless terminal W that considers: i. the topology of the adjacency graph; and ii. the calendrical time T; and iii. the environmental conditions /V; and iv. the natural and man-made physical attributes that affect the location and movement of wireless terminals and the entities that carry them (e.g., buildings, sidewalks, roads, tunnels, bridges, hills, walls, water, cliffs, rivers, etc.); and v. the legal laws governing the location and movement of wireless terminals and the entities that carry them (e.g., one-way streets, etc.); and vi. the past data for the movement of all wireless terminals; and vii. the past data for the movement of wireless terminal W.
  • a model of the movement of wireless terminal W that considers: i. the topology of the adjacency graph; and
  • the moving probabilities P M ⁇ , T, N, W, C) associated with a location b can be considered to be either isotropic or non-isotropic.
  • isotropic moving probabilities are defined as those which reflect a uniform likelihood of direction of movement
  • non-isotropic moving probabilities are defined as those which reflect a non-uniform likelihood of direction of movement.
  • the values of P M (b, T, N, W, c) are non- isotropic if there are at least two probabilities with different values.
  • the values of P M ⁇ , T, N, W, c) are isotropic if and only if:
  • Isotropic moving probabilities are simple to generate, but are considerably less accurate than non-isotropic moving probabilities that are generated in consideration of the above criteria. Therefore, in accordance with the illustrative embodiment, the moving probabilities are non-isotropic, but it will be clear to those skilled in the art, after reading this disclosure, how to make and use alternative embodiments of the present invention that use isotropic moving probabilities.
  • Populating Trait-Correction Database 313 - Figure 7 depicts a flowchart of the salient processes performed as part of process 402: populating Trait- Correction Database 313.
  • location server 214 In general, the ability of location server 214 to estimate the location of wireless terminal 201 is limited by the accuracy with which the traits are measured by wireless terminal 201 and by base stations 202-1, 202-2, and 202-3. When the nature or magnitude of the measurement errors is unpredictably inaccurate, there is little that can be done to overcome them. [0088] In contrast, when the nature and magnitude of the measurement errors are predictable, they can be corrected, and the nature and magnitude of some measurement errors are, in fact, predictable. For example, one make and model of wireless terminal is known to erroneously measure and report the signal strength of signals by -2 dB.
  • this -2 dB error could cause location server 214 to erroneously estimate the location of the wireless terminal.
  • location server 214 adds 2 dB to the measurements from that make and model of wireless terminal, the likelihood that location server 214 would erroneously estimate the location of the wireless terminal would be reduced.
  • Trait-Correction Database 313 comprises the information needed by location server 214 to be aware of systemic measurement errors and to correct them. A technique for eliminating some situational errors in the measurements is described below and in the accompanying figures.
  • a distortion function is generated for every radio that might provide measurements to location server 214 and for every trait whose measurements can be erroneous.
  • the distortion function D(A,K,Q) relates the reported measurement R for a trait Q to the actual value A for that trait and the defining characteristic K of the radio making the measurement:
  • the distortion function D(A,K,Q) is provided to the owner/operator of location server 214 by the radio manufacturer. It will be clear to those skilled in the art, however, after reading this disclosure, how to generate the distortion function D(A,K,Q) for any radio without the assistance of the radio manufacturer.
  • FIG. 8a An ideal radio perfectly measures and reports the value of the traits it receives and the distortion function D(A,K,Q) for one trait and for an ideal radio is depicted in Figure 8a.
  • the salient characteristic of an ideal radio is that the reported value of the measurement, R, is exactly equal to the actual value of the trait /4 at the radio (i.e., there is np. measurement or reporting error).
  • Figure 8b depicts a graph of the distortion function of an illustrative real-world radio. In this case, the reported measurement is too high for some values, too low for others, and correct for only one value.
  • the distortion function D(A,K,Q) for all measurements is represented in tabular form.
  • the distortion function for one type of signal-strength measurement for various radios is shown in Table 1. It will be clear to those skilled in the art, after reading this disclosure, however, how to make and use alternative embodiments of the present invention in which the distortion function for some or all measurements is not represented in tabular form. Furthermore, it will be clear to those skilled in the art, after reading this disclosure, how to make and use alternative embodiments of the present invention that comprise distortion functions for any type of measurement of any type of trait and for any radio.
  • the purpose of the characteristic, K is to identify which calibration function should be used in calibrating the reported measurements from wireless terminal 201, and, therefore, the characteristic, K 1 should be as indicative of the actual distortion function for wireless terminal 201 as is economically reasonable.
  • the characteristic, K can be, but is not limited to: i. the unique identity of wireless terminal 201 (e.g., its electronic serial number (“ESN”), its international mobile station identifier ("IMSI”), its temporary international mobile station identifier (“TIMSI”), mobile station identification ("MSID”), its directory number (“DN”), etc.); or ii. the model of wireless terminal 201 ⁇ e.g., Timeport 210c, etc.); or iii. the make ⁇ i.e., manufacturer) of wireless terminal 201 (e.g., Motorola,
  • wireless terminal 201 e.g., Samsung, Nokia, etc.
  • the identity of the radio-frequency circuitry of wireless terminal 201 e.g.,
  • the most accurate characteristic is the unique identity of wireless terminal 201 because that would enable location server 214 to use the calibration function generated for that very wireless terminal. It is unlikely, however, that this is economically feasible because it would require that every wireless terminal be tested to determine its own unique distortion function.
  • K 1 is economically reasonable, but it is unlikely that a single calibration function for all of a manufacturer's wireless terminals would provide very accurate calibrated signal-strength measurements.
  • the illustrative embodiment uses the combination of make and model of wireless terminal 201 as the characteristic, K, because it is believed that the amount of variation between wireless terminals of the same make and model will be small enough that a single calibration function for that model should provide acceptably accurate calibrated measurements for every wireless terminal of that make and model.
  • the calibration function C(R,K,Q) is generated for every radio that might provide measurements to location server 214 and for every trait whose measurements can be distorted.
  • the calibration function C(R,K,Q) relates the calibrated measurement S of a trait Q 1 to the reported measurement R of trait Q and the defining characteristic K of the radio making the measurement:
  • the calibration function C(R,K,Q) is the inverse of the distortion function D(A,K,Q).
  • the salient characteristic of the calibration function C(R, K 1 Q) is that it satisfies the equation 3:
  • the function C(R,K,Q) is represented in tabular form, such as that shown in Table 2.
  • the calibration functions C(R,K,Q) are stored in Trait-Corrections Database 313.
  • Maintaining Location-Trait Database 313 - Figure 9 depicts a flowchart of the salient processes performed in process 403: maintaining Location -Trait Database 313 and Trait-Corrections Database 314.
  • the ability of the illustrative embodiment to function is based on - and limited by - the accuracy, freshness, and completeness of the information contained in Location-Trait Database 313 and Trait- Corrections Database 314.
  • a drive-test regimen is developed that periodically makes empirical measurements throughout geographic region 220 with highly-accurate equipment to ensure the accuracy, freshness, and completeness of the information contained in Location-Trait Database 313 and Trait-Corrections Database 314.
  • Estimating the Location of Wireless Terminal 201 - Figure 10 depicts a flowchart of the salient processes performed in process 403: estimating the location of wireless terminal 201.
  • process 403 is initiated by a request from location client 213 for the location of wireless terminal 201. It will be clear to those skilled in the art, however, after reading this disclosure, how to make and use alternative embodiments of the present invention in which process 403 is initiated periodically, sporadically, or in response to some other event.
  • Y probability distributions for the location of wireless terminal 201 are generated for each of instants H 1 through H ⁇ in the temporal interval ⁇ T, wherein Y is a positive integer, based on comparing the measurements of traits associated with wireless terminal 201 at each of instants H 1 through H ⁇ to expected values for those traits at those times.
  • Each of the Y probability distributions provides a first estimate of the probability that wireless terminal 201 is in each location at each of instants H 1 through Hy.
  • Z probability distributions for the location of wireless terminal 201 are generated for each of instants A 1 though Az in the temporal interval ⁇ T, wherein Z is a positive integer, based on Assisted GPS measurements at wireless terminal 201 at each of instants A 1 though A z -
  • Each of the Z probability distributions provides a first estimate of the probability that wireless terminal 201 is in each location at each of instants A 1 though A z .
  • process 1003 the Y probability distributions generated in process 1001 and the Z probability distributions generated in process 1002 are combined, taking into account their temporal order, to generate a second estimate of the location of wireless terminal 201.
  • the details of process 1003 are described below and in the accompanying figures.
  • location server 214 receives Y nonempty sets of measurements of the traits, M 1 though My, associated with wireless terminal 201. Each set of measurements is made at one of instants H 1 through H ⁇ .
  • each set of measurements comprises: i. the pathloss of all of the signals received by wireless terminal 201 from all transmitters ⁇ e.g., base stations 202-1, 202-2, and 202-3, commercial television, commercial radio, navigation, ground-based aviation, etc.); and ii. the pathloss of all of the signals transmitted by wireless terminal 201 as received at base stations 202-1, 202-2, and 202-3; and iii. the received signal strength of all of the signals received by wireless terminal 201 from all transmitters; and iv. the received signal strength of all of the signals transmitted by wireless terminal 201 as received at base stations 202-1, 202-2, and 202-3; and v.
  • the received signal-to-impairment ratio of all of the signals received by wireless terminal 201 from all transmitters and vi. the received signal-to-impairment ratio of all of the signals transmitted by wireless terminal 201 as received at base stations 202-1, 202-2, and 202-3; and vii. the received temporal difference of each pair of multipath components of all of the signals received by wireless terminal 201 from all transmitters; and viii. the received temporal difference of each pair of multipath components of all of the signals transmitted by wireless terminal 201 as received at base stations 202-1, 202-2, and 202-3; and ix. the received delay spread of all of the signals received by wireless terminal 201 from all transmitters; and x.
  • the handover state e.g., soft, softer, Ix, 2x, etc.
  • wireless terminal 201 provides its measurements directly to location server 214 via the user plane and in response to a request from location server 214 to do so. This is advantageous because the quality of the estimate of the location of wireless terminal 201 is enhanced when there are no limitations on the nature, number, or dynamic range of the measurements - as might occur when measurements are required to be made in accordance with the air-interface standard. It will be clear to those skilled in the art, however, after reading this disclosure, how to make and use alternative embodiments of the present invention in which wireless terminal 201 provides its measurements periodically, sporadically, or in response to some other event. Furthermore, it will be clear to those skilled in the art, after reading this disclosure, how to make and use alternative embodiments of the present invention in which wireless terminal 201 provides its measurements to location server 214 via the UMTS protocol.
  • base stations 202-1, 202- 2, and 202-3 provide their measurements to location server 214 via wireless switching center 211 and in response to a request from location server 214 to do so. It will be clear to those skilled in the art, however, after reading this disclosure, how to make and use alternative embodiments of the present invention in which base stations 202-1, 202- 2, and 202-3 provide their measurements to location server 214 periodically, sporadically, or in response to some other event.
  • location server 214 also receives from wireless terminal 201: i. the identities of the base stations that provided service to wireless terminal 201 at each of instants H 1 through H Yr and ii. the identities of the neighboring base stations that provided service to the location of wireless terminal 201 at each of instants H 1 through H ⁇ . This information is used by location server 214 in performing search area reduction, which is described in detail below.
  • location server 214 uses the calibration functions C(R,K,Q) in the Trait-Corrections Database 314 to correct the systemic errors in the measurements received in process 1001.
  • location server 214 computes the differentials, in those cases that are appropriate, of the measurements to correct the situational errors in the measurements received in process 1001. Many factors, including the condition of wireless terminal 201's antenna, the state of its battery, and whether or not the terminal is inside a vehicle can introduce situational measurement errors. This is particularly true for measurements of pathloss and signal strength.
  • the illustrative embodiment ameliorates the effects of these factors by pattern matching not the measurements themselves - whether corrected in process 1102 or not - to the expected values for those traits, but by pattern matching the pair-wise differentials of those measurements to the pair-wise differentials of the expected values for those traits. It will be clear to those skilled in the art, after reading this disclosure, how to make and use alternative embodiments of the present invention in which different measurements are corrected for situational errors by the use of pair- wise differentials.
  • a simple example involving signal strengths illustrates this approach.
  • a first radio station, Radio Station A can be received at -56 dBm at Location 1, -42 dBm at Location 2, -63 dBm at Location 3, and -61 dBm at Location 4, and a second radio station, Radio Station B, can be received at -63 dBm at Location 1, -56 dBm at Location 2, -65 dBm at Location 3, and -52 dBm at Location 4.
  • This information is summarized in the table below and forms the basis for a map or database that correlates location to signal strength.
  • a given wireless terminal with a broken antenna and at an unknown location receives Radio Station A at -47 dBm and Radio Station B at -61 dBm, then it registers Radio Station A as 14 dBm stronger than Radio Station B. This suggests that the wireless terminal is more likely to be at Location 2 than it is at Location 1, 3, or 4. If the measured signal strengths themselves were pattern matched into Location -Trait Database 313,. the resulting probability distribution for the location of wireless terminal 201 might not be as accurate.
  • a disadvantage of this approach is that the situational bias is eliminated at the expense of (1) doubling the variance of the random measurement noise, and (b) reducing the number of data points to pattern match by one. Furthermore, the pair-wise subtraction introduces correlation into the relative signal strength measurement errors (Ae., all of the data points to be matched are statistically correlated). It will be clear to those skilled in the art how to account for this correlation in calculating the likelihood of the measurement report.
  • location server 214 performs a technique called "search area reduction" in preparation for process 1105. To understand what search area reduction is and why it is advantageous, a brief discussion of process 1105 is helpful.
  • location server 214 estimates the probability that wireless terminal 201 is in each location at each of instants H 1 through H ⁇ . This requires generating Y multi-dimensional probability distributions, one for each of instants H x through Hy.
  • the process for generating each multi-dimensional probability distribution can be computationally intensive and the intensity depends on the number of locations that must be considered as possible locations for wireless terminal 201.
  • the process can be performed quickly enough for many "real-time” applications. In contrast, when the number of locations that must be considered is large, the process can often take too long.
  • geographic region 220 comprises only 28 locations. In many alternative embodiments of the present invention, however, geographic region 220 comprises thousands, millions, or billions of locations. The consideration of thousands, millions, or billions of locations for each instant by location server 214 might take too long for many real-time applications.
  • location server 214 performs some computationally-efficient tests that quickly and summarily eliminate many possible locations for wireless terminal 201 from consideration, and, therefore, summarily set to zero the probability that wireless terminal 201 is at those locations. This reduces the number of locations that must be fully considered in process 1105 and generally improves the speed with which process 1001 is performed.
  • location server 214 uses six computationally efficient tests in an attempt to designate one or more locations as improbable locations for wireless terminal 201.
  • a location that is designated as improbable by one or more of the six tests at instant H 1 is designated as improbable by process 1104 at instant H 1 .
  • the computational burden on location server 214 of generating the probability distribution for that instant is reduced.
  • the first type of error - a Type I error - occurs when process 1104 designates a location as improbable when, in fact, it is not improbable for wireless terminal 201 to be in that location.
  • the second type of error - a Type II error - occurs when process 1104 fails to designate a location as improbable when, in fact, it is improbable that wireless terminal 201 is in that location.
  • a Type I error affects the accuracy with which the illustrative embodiment can estimate the location of wireless terminal 201
  • a Type II error affects the speed with which processor 1104 can generate the probability distributions.
  • the tests and their parameters are chosen to balance the number of Type I and Type II errors with the computational complexity and value of process 1104. For example, when there are too many Type II errors, the value of process 1104 is undermined by the computational burden of process 1104. It will be clear those skilled in the art, after reading this disclosure, how to make and use alternative embodiments of the present invention that have any number of Type I and Type II errors.
  • Figure lib depicts a flowchart of the salient processes performed in accordance with process 1104: search area reduction.
  • location server 214 designates a location as improbable when the difference between a measured value of a trait and the expected value of that trait at that location exceeds a threshold.
  • location engine 214 performs process 1111 on each measured value of each trait for each signal for each of instants H 1 through Hy. It will be clear to those skilled in the art, after reading this disclosure, how to choose the traits and signals and thresholds to achieve the desired number of Type I and Type II errors. It will be clear to those skilled in the art, after reading this disclosure, how to make and use alternative embodiments of the present invention that omit process 1111 or that omit testing one or more traits and/or one or more signals in process 1111.
  • location server 214 designates that location as improbable when a ranking of the two measurements differs from a ranking of the expected values.
  • location engine 214 performs process 1112 on each pair of measurements of each trait for each of instants H 1 through H ⁇ .
  • location server 214 designates a location as improbable when a measurement of traits of a signal is not received when it is expected if wireless terminal 201 were, in fact, in that location.
  • location engine 214 performs process 1113 on each trait of each expected signal for each of instants H 1 through H ⁇ . This test is highly prone to Type I errors and should be used judiciously. It will be clear to those skilled in the art, after reading this disclosure, how to make and use alternative embodiments of the present invention that omit process 1113 or that omit testing one or more traits and/or one or more signals in process 1113.
  • location sever 214 designates a location as improbable when a measurement of a trait of a signal is received when it is not expected if wireless terminal 201 were, in fact, in that location.
  • location engine 214 performs process 1114 on each trait of each signal for each of instants Hi through H ⁇ . In general, this test is less prone to Type I errors than the test in process 1113. It will be clear to those skilled in the art, after reading this disclosure, how to make and use alternative embodiments of the present invention that omit process 1114 or that omit testing one or more traits and/or one or more signals in process 1114.
  • location server 214 designates a location as improbable when the location is not provided wireless telecommunications service by a base station that is known to be providing service to wireless terminal 201 at that instant.
  • the theory underlying this test is that if a base station that provided telecommunications service to wireless terminal 201 at that instant does not provide service to the location, then it suggests that wireless terminal 201 is not in that location at that instant. In general, this test is highly accurate and has a low number of both Type I and Type II errors. It will be clear to those skilled in the art, after reading this disclosure, how to make and use alternative embodiments of the present invention that omit process 1115.
  • location server 214 designates a location as improbable designating a possible location as improbable when the location is not within the neighboring coverage area of a base station that is known to be a neighboring base station of wireless terminal 201.
  • the theory underlying this test is that if a location is not within the neighboring coverage area of a base station that is a neighbor of wireless terminal 201 at that instant, then it suggests that wireless terminal 201 is not in the location at that instant. In general, this test is highly accurate and has a low number of both Type I and Type II errors. It will be clear to those skilled in the art, after reading this disclosure, how to make and use alternative embodiments of the present invention that omit process 1116. [0142] A location that that is designated as improbable at instant H,- by one or more of processes 1111 through 1116 is designated as improbable by process 1104 at instant H 1 .
  • location server 214 generates each of the Y probability distribution for that wireless terminal 201 at each of instants H 1 through H ⁇ . To accomplish this, location server 214 performs the processes described below and in Figure lie.
  • Figure lie depicts a flowchart of the salient processes performed in accordance with process 1105: generating the Y probability distribution for that wireless terminal 201 at each of instants H 1 through H Y .
  • location server 214 sets the probability of wireless terminal 201 being at a location at instant H, to zero (0) if the location was designated as improbable at instant H 1 by process 1104.
  • location server 214 generates the Euclidean norm between the measurements of a trait and the expected values for that trait at all instants and for all locations not designated as improbable by process 1104.
  • the E ⁇ uclidean norm is generated between the measurements (as corrected in process 1102, if necessary and/or the differentials of measurements as the case may be) of the expected values for those traits in Lo cation -Trait Database 313.
  • the Euclidean norm is generated as described in Equation 4:
  • V ⁇ .H. ⁇ ((E(b, H 1 , N, W, Q) - M ⁇ b, H 1 , N, W, Q)) ⁇ (Q)f (Eq. 4)
  • V(b,H ⁇ ) is the Euclidean norm for Location b at instant H, based on the square root of the sum of the square of the differences between each (corrected and differential, where appropriate) trait measurement M(b, Hi, N, W, Q) minus the expected value E(b, H 1 , N, W, Q) for that trait
  • ⁇ (Q) is a weighting factor that indicates the relative weight to be given discrepancies in one trait versus discrepancies in the other traits.
  • the un-normalized probabilities of the location of wireless terminal 201 at each location are generated based on the Euclidean norms generated in process 1122 as shown in Equation 5.
  • UP(O 1 Hj) Q (Eq. 5) wherein UP ⁇ b,Hj) represents the un-normalized probability that wireless terminal 201 is in Location b at instant H, , and wherein ⁇ % equals:
  • location server 214 generates a preliminary estimate of the location of wireless terminal 201 at instant H 1 based on the maximum likelihood function of the normalized probability distribution at instant H 1 .
  • location server 214 transmits, and assistance server 212 receives, the preliminary estimate of the location of wireless terminal 201 at instant H 1 as generated in process 1105.
  • assistance server 212 generates assistance data for wireless terminal 201 based on the preliminary estimate of the location of wireless terminal 201 at instant H 1 .
  • assistance server 212 generates "fully-custom" assistance data based on the estimate of the location of wireless terminal 201 at instant H 1 .
  • the assistance data is "fully-custom” because it is specifically tailored to the estimated location of wireless terminal 201 at instant H 1 , It will be clear to those skilled in the art how to generate fully-custom assistance data for wireless terminal 201 based on the estimated location of wireless terminal 201 at instant H 1 .
  • assistance server 212 transmits the assistance data to wireless terminal 201 via wireless switching center 212 in well-known fashion.
  • assistance server 212 pre-computes assistance data for a plurality of diverse locations within geographic region 220 and selects that pre-computed assistance data for wireless terminal 201 based on the estimated location of wireless terminal 201 at instant H 1 . Because the assistance data selected for wireless terminal 201 is not specifically tailored to the estimated location of wireless terminal 201 at instant H 1 , nor generic to all of geographic region 220 or to the cell or sector of the base station serving wireless terminal 201, it is deemed "semi-custom" assistance data.
  • semi-custom assistance data is less accurate than fully-custom assistance data, but more accurate, on average, than generic assistance data, which is chosen based on cell ID alone and that is based on one location within geographic region 220. It will be clear to those skilled in the art, after reading this disclosure, how to generate the fully-custom and semi-custom assistance data for wireless terminal 201.
  • wireless terminal 201 receives the assistance data from assistance server 212, in well-known fashion, (b) uses it to facilitate the acquisition and processing of one or more GPS satellite signals in well- known fashion, and (c) transmits Z non-empty sets of GPS-derived information to location server 214 for readings at instants G 1 through G Zr where Z is a positive integer.
  • each set of GPS-derived information comprises: i. a GPS-derived estimate of the location of wireless terminal 201
  • ranging data e.g., PRN code phase, etc.
  • GPS satellites or iii. parti a I Iy- processed ranging signals ⁇ e.g., signals from which the ranging data has not yet been extracted, etc.) from one or more GPS satellites, or iv. any combination of i, ii, and iii.
  • location server 214 receives Z nonempty sets of GPS-derived information to location server 214 for readings at instants G 1 through G 2 and generates a probability distribution that indicates the likelihood that wireless terminal 201 is in each location at each of instants G 1 through G z . It will be clear to those skilled in the art how to perform process 1204.
  • Figure 13 depicts a flowchart of the salient processes performed in process 1003 - combining the Y non-GPS-based probability distributions with the Z GPS- based probability distributions to derive F refined multi-dimensional probability distributions for the location of wireless terminal 201 at each of instants Ji through J F , where each J, corresponds to one of: i.
  • each "composite" instant J,- corresponds to either an instant associated with a non-GPS-based probability distribution, or an instant associated with a GPS-based probability distribution, or an instant associated with both a non-GPS probability distribution-and a GPS-based probability distribution.
  • the Y non-GPS-based probability distributions with the Z GPS-based probability distributions are intelligently combined, taking into consideration their relative temporal occurrence to derive a refined multidimensional probability distribution for the location of wireless terminal 201 at instants Ji through J F .
  • the number of composite instants F is at most Y plus Z, and is at least the maximum of Y and Z - the former occurring when there are no coincident GPS/non-GPS probability distributions, and the latter when there are as many as possible coincident GPS/non-GPS probability distributions.
  • Figure 15 depicts a second example of determining each of instants Ji through J F based on non-GPS-based instants and GPS-based instants. This second example illustrates that even when the non-GPS-based instants are uniformly spaced in time and the GPS-based instants are uniformly spaced in time, the composite instants are no_t necessarily uniformly spaced in time.
  • the time step ⁇ t is defined as the minimum time interval between any two instants.
  • the time step is atomic in that the time difference between any two instants is an integral multiple of time steps. (Note that two consecutive instants - whether they are non-GPS-based instants, GPS-based instants, or composite instants - might be more than a single time step apart.)
  • the time step of the present invention is therefore similar to the time step employed in clock- driven discrete event simulations.
  • time step ⁇ t typically will depend on the particular application, and involves a tradeoff between (1) temporal precision and (2) available memory and processing power.
  • the selected time step can affect the definition of locations, the moving and staying probabilities, and consequently the graphs that are derived from them ⁇ e.g., the adjacency graph, etc.).
  • location server 214 determines instants J 1 through J F , as described above.
  • location server 214 constructs unrefined probability distributions V 1 through V F for instants Ji through J F as follows: i. if J 1 corresponds to a particular H j only, then V 1 equals the non-GPS probability distribution at instant H j , ii. if J/ corresponds to a particular G ⁇ only, then Vi equals the GPS probability distribution at instant G k , and iii. otherwise (C,- corresponds to both a particular H j and a particular G k ), Vi equals a probability distribution that equals the normalized product of the non-GPS and GPS probability distributions at instant J 1 .
  • location server 214 determines for each instant J 1 -, temporally-extrapolated probability distributions Dy for aU j ' ⁇ i, 1 ⁇ j ⁇ F, which are based on (i) the unrefined probability distribution V j at instant Jj, (ii) P s (b, T, N, W) 1 and (iii) T, N, W, C).
  • the extrapolated probability distribution D, r j is therefore a predictive probability distribution at instant J,- that is based on empirical data at instant J j - but not on any empirical data at other instants, including J 1 . i. the past data for the movement of all wireless terminals; and ii. the past data for the movement of wireless terminal W; and iii. the location, speed, and acceleration of wireless terminal W at calendrical time 7 " ; and iv. the state of traffic signals that can affect the movement of wireless terminals in location b.
  • a temporally-extrapolated probability distribution can be progressed ⁇ i.e., projected into the future based on a past probability distribution). For example, if instant J 3 is one time step after instant Jz, then extrapolated probability distribution D3, 2 is derived by a single application of Ps(b, T, N r W) and P M (b, T, N, W, c) to unrefined probability distribution V 2 . In other words, for any location b:
  • V 3 Ib ] D 2/3 [6] - P s ⁇ , J 21 N 1 W) + ⁇ D 2r3 ⁇ c ⁇ - .
  • Equation 8 can be applied iteratively in well-known fashion. (Because the time step is atomic the number of iterations is always integral.) As will be further appreciated by those skilled in the art, after reading this disclosure, the extrapolated probability distributions for non- consecutive time instants (e.g., D 2 ,4, Ds 1I1 etc.) can be efficiently computed in a bottom- up fashion from the extrapolated probability distributions for consecutive time instants via dynamic programming.
  • Equation 10 in expanded form yields:
  • location server 214 generates an estimate of the location of wireless terminal 201 at one or more instants J,- based on the maximum likelihood function of L 1 . (As will be appreciated by those skilled in the art, after reading this disclosure, in some other embodiments of the present invention an estimate might be generated from probability distribution L 1 using another function or method.)
  • location server 214 provides the estimate(s) of the location of wireless terminal 201 generated in process 1305 to location client 213, in well-known fashion.

Abstract

A method of using a non-GPS-derived technique to estimate the location of an Assisted-GPS-enabled wireless terminal for the purposes of generating location -specific assistance data for the wireless terminal is disclosed. The wireless terminal then uses the assistance data to acquire and process one or more GPS signals and to derive information that is probative of the wireless terminal's location. The GPS-derived location information is then combined with non-GPS-derived location to form an estimate of the location of the wireless terminal that is better than can be derived from either alone. This combination of GPS-derived and non-GPS techniques is particularly useful when the wireless terminal can only acquire one or two GPS signals because it is not possible to determine the location of the wireless terminal with only two GPS signals alone.

Description

Estimating the Location of a Wireless Terminal Based on Assisted
GPS and Pattern Matching
Field of ths Invention
[oooi] The present invention relates to telecommunications in general, and, more particularly, to a technique for estimating the location of a wireless terminal and using the estimate of the location in a location-based application.
Background
[0002] Figure 1 depicts a diagram of the salient components of wireless telecommunications system 100 in accordance with the prior art. Wireless telecommunications system 100 comprises: wireless terminal 101, base stations 102-1, 102-2, and 102-3, wireless switching center 111, assistance server 112, location client 113, and Global Positioning System ("GPS") constellation 121. Wireless telecommunications system 100 provides wireless telecommunications service to all of geographic region 120, in well-known fashion.
[0003] The salient advantage of wireless telecommunications over wireline telecommunications is the mobility that is afforded to the users. On the other hand, the salient disadvantage of wireless telecommunications lies in that fact that because the user is mobile, an interested party might not be able to readily ascertain the location of the user.
[0004] Such interested parties might include both the user of the wireless terminal and remote parties. There are a variety of reasons why the user of a wireless terminal might be interested in knowing his or her location. For example, the user might be interested in telling a remote party where he or she is or might seek advice in navigation.
[0005] In addition, there are a variety of reasons why a remote party might be interested in knowing the location of the user. For example, the recipient of an E 9-1-1 emergency call from a wireless terminal might be interested in knowing the location of the wireless terminal so that emergency services vehicles can be dispatched to that location.
[0006] There are many techniques in the prior art for estimating the location of a wireless terminal. [0007] In accordance with one technique, the location of a wireless terminal is estimated to be at the center of the cell or centroid of the sector in which the wireless terminal is located. This technique is advantageous in that it does not require that additional hardware be added to the wireless terminal or to the wireless telecommunications system, and, therefore, the first technique can be inexpensively implemented in legacy systems. The first technique is only accurate (in present cellular systems), however, to within a few kilometers, and, therefore, it is generally not acceptable for applications (e.g., emergency services dispatch, etc.) that require higher accuracy.
[0008] In accordance with a second technique, the location of a wireless terminal is estimated by triangulating the angle of arrival or multilaterating the time of arrival of the signals transmitted by the wireless terminal. This technique can achieve accuracy to within a few hundreds of meters and is advantageous in that it can be used with legacy wireless terminals. The disadvantage of this second technique, however, is that it generally requires that hardware be added to the telecommunication system's base stations, which can be prohibitively expensive.
[0009] In accordance with a third technique, the location of a wireless terminal is estimated by a radio navigation unit, such as, for example, a Global Positioning System (GPS) receiver, that is incorporated into the wireless terminal. This technique is typically accurate to within tens of meters but is disadvantageous in that it does not work consistently well indoors, in heavily wooded forests, or in urban canyons. Furthermore, the accuracy of this third technique can be severely degraded by multipath reflections.
[OOio] Therefore, the need exists for a technique for estimating the location of a wireless terminal with higher resolution than the first technique and without some of the costs and disadvantages of the second and third techniques.
Summary of the Invention
[ooii] The present invention enables the construction and use of a system that can estimate the location of a wireless terminal without some of the costs and limitations associated with techniques for doing so in the prior art.
[0012] The present invention is based on the recognition that there are traits of electromagnetic signals that are dependent on topography, the receiver, the location of the transmitter, and other factors. For example, if a particular radio station is known to be received strongly at a first location and weakly at a second location, and a given wireless terminal at an unknown location is receiving the radio station weakly, it is more likely that the wireless terminal is at the second location than at the first location. [0013] By quantifying "strongly" and "weakly" and extending this principle to multiple traits and multiple signals, the present invention can estimate the location of a wireless terminal with greater accuracy.
[0014] The illustrative embodiment comprises: generating a first non-GPS-derived estimate of the location of a wireless terminal based on a first measurement of a trait of a first signal; and generating assistance data for a satellite signal that is received by the wireless terminal, wherein the assistance data is based on the first non-GPS-derived estimate of the location of the wireless terminal.
Brief Description of the Drawings
[0015] Figure 1 depicts a map of a portion of a wireless telecommunications system in the prior art.
[0016] Figure 2 depicts a diagram of the salient components of wireless telecommunications system 200 in accordance with the illustrative embodiment of the present invention.
[0017] Figure 3 depicts a block diagram of the salient components of location server 214, as shown in Figure 2, in accordance with the illustrative embodiment.
[0018] Figure 4 depicts a flowchart of the salient processes performed in accordance with the illustrative embodiment of the present invention.
[0019] Figure 5 depicts a flowchart of the salient processes performed in accordance with process 401 of Figure 4: building Location-Trait Database 313.
[0020] Figures 6a through 6k depict geographic regions and their deconstruction into a plurality of locations.
[0021] Figure 6L depicts an alternative partitioning of geographic region 220 into 64 square locations.
[0022] Figure 6m depicts a graphical representation of an adjacency graph of geographic region 220 as partitioned in Figures 6c through 6e.
[0023] Figure 6n depicts a graphical representation of an adjacency graph of the highway intersection partitioned in Figures 6h through 6k.
[0024] Figure 7 depicts a flowchart of the salient processes performed as part of process 402 of Figure 4: populating Trait-Correction Database 313.
[0025] Figures 8a through 8c depict illustrative distortion and correction curves.
[0026] Figure 9 depicts a flowchart of the salient processes performed in process 403 (of Figure 4): maintaining Location-Trait Database 313.
[0027] Figure 10 depicts a flowchart of the salient processes performed in process 701 of Figure 7: estimating the location of wireless terminal 201. [OO28] Figure lla depicts a flowchart of the salient processes performed in process 901 of Figure 9: generating the probability distribution for the location of wireless terminal 201 based on the traits of one or more signals received by, or transmitted to, wireless terminal 201 at instants H1 through Hγ.
[0029] Figure lib depicts a flowchart of the salient processes performed in accordance with process 1104 of Figure lla: search area reduction.
[0030] Figure lie depicts a flowchart of the salient processes performed in accordance with process 1105: generating the probability distribution for that wireless terminal 201 at each of instants H1 through Hγ.
[0031] Figure 12 depicts a flowchart of the salient processes performed in process 902 of Figure 9: generating the probability distribution for the location of wireless terminal 201 based on GPS-derived information (i.e., information from GPS constellation 221).
[O032] Figure 13 depicts a flowchart of the salient processes performed in process 903 of Figure 9: combining non-GPS-based and GPS-based probability distributions for the location of wireless terminal 201.
[0033] Figure 14 depicts a first example of combining non-GPS-based instants H1 through /Vy and GPS-based instants Gi through Gz into composite instants J1 through Jf.
[0034] Figure 15 depicts a second example of combining non-GPS-based instants H1 through Hy and GPS-based instants G1 through Gz into composite instants J1 through JF-
Detailed Description
[0035] For the purposes of this specification, the following terms and their inflected forms are defined as follows:
• The term "location" is defined as a one-dimensional point, a two-dimensional area, or a three-dimensional volume.
• The term "staying probability" is defined as an estimate of the probability Ps(b, T, N, W) that wireless terminal W in location b at calendrical time T will still be in location b at time T+Δt, given environmental conditions, N.
• The term "moving probability" is defined as an estimate of the probability P/vib, T, N, W, c) that wireless terminal W in location b at calendrical time T will be in adjacent location c at time T+Δt, given environmental conditions, N.
• The term "environmental conditions N," are defined to include one or more physical aspects of the environment, and includes, but is not limited to, the weather, the astronomical conditions, atmospheric conditions, the quantity and density of radio traffic, the quantity and density of vehicular traffic, road and sidewalk construction, etc.
• The term "calendrical time T" is defined as the time as denominated in one or more measures (e.g., seconds, minutes, hours, time of day, day, day of week, month, month of year, year, etc.).
[0036] Overview - Figure 2 depicts a diagram of the salient components of wireless telecommunications system 200 in accordance with the illustrative embodiment of the present invention. Wireless telecommunications system 200 comprises: wireless terminal 201, base stations 202-1, 202-2, and 202-3, wireless switching center 211, assistance server 212, location client 213, location server 214, and GPS constellation 221, which are interrelated as shown. The illustrative embodiment provides wireless telecommunications service to all of geographic region 220, in well- known fashion, estimates the location of wireless terminal 201 within geographic region 220, and uses that estimate in a location-based application.
£0037] In accordance with the illustrative embodiment, wireless telecommunications service is provided to wireless terminal 201 in accordance with the Universal Mobile Telecommunications System, which is commonly known as "UMTS." After reading this disclosure, however, it will be clear to those skilled in the art how to make and use alternative embodiments of the present invention that operate in accordance with one or more other air-interface standards (e.g., Global System Mobile "GSM," CDMA-2000, IS-136 TDMA, IS-95 CDMA, 3G Wideband CDMA, IEEE 802.11 WiFi, 802.16 WiMax, Bluetooth, etc.) in one or more frequency bands.
[0038] Wireless terminal 201 comprises the hardware and software necessary to be UMTS-compliant and to perform the processes described below and in the accompanying figures. For example and without limitation, wireless terminal 201 is capable of: i. measuring one or more traits of one of more electromagnetic signals and of reporting the measurements to location server 214, and ii. transmitting one or more signals and of reporting the transmission parameters of the signals to location server 214, and iii. receiving GPS assistance data from assistance server 212 to assist it in acquiring and processing GPS ranging signals.
Wireless terminal 201 is mobile and can be at any location within geographic region 220. Although wireless telecommunications system 200 comprises only one wireless terminal, it will be clear to those skilled in the art, after reading this disclosure, how to make and use alternative embodiments of the present invention that comprise any number of wireless terminals.
[0039] Base stations 202-1, 202-2, and 202-3 communicate with wireless switching center 211 and with wireless terminal 201 via radio in well-known fashion. As is well known to those skilled in the art, base stations are also commonly referred to by a variety of alternative names such as access points, nodes, network interfaces, etc. Although the illustrative embodiment comprises three base stations, it will be clear to those skilled in the art, after reading this disclosure, how to make and use alternative embodiments of the present invention that comprise any number of base stations.
[0040] In accordance with the illustrative embodiment of the present invention, base stations 202-1, 202-2, and 202-3 are terrestrial, immobile, and within geographic region 220. It will be clear to those skilled in the art, after reading this disclosure, how to make and use alternative embodiments of the present invention in which some or all of the base stations are airborne, marine-based, or space-based, regardless of whether or not they are moving relative to the Earth's surface, and regardless of whether or not they are within geographic region 220.
[0041] Wireless switching center 211 comprises a switch that orchestrates the provisioning of telecommunications service to wireless terminal 201 and the flow of information to and from location server 214, as described below and in the accompanying figures. As is well known to those skilled in the art, wireless switching centers are also commonly referred to by other names such as mobile switching centers, mobile telephone switching offices, routers, etc.
[0042] Although the illustrative embodiment comprises one wireless switching center, it will be clear to those skilled in the art, after reading this disclosure, how to make and use alternative embodiments of the present invention that comprise any number of wireless switching centers. For example, when a wireless terminal can interact with two or more wireless switching centers, the wireless switching centers can exchange and share information that is useful in estimating the location of the wireless terminal. For example, the wireless switching centers can use the IS-41 protocol messages Handof fMeasurementRequest and Handof fMeasurementRequest2 to elicit signal-strength measurements from one another. The use of two or more wireless switching centers is particularly common when the geographic area serviced by the wireless switching center is small (e.g., local area networks, etc.) or when multiple wireless switching centers serve a common area.
[0043] In accordance with the illustrative embodiment, all of the base stations servicing wireless terminal 201 are associated with wireless switching center 211. It will be clear to those skilled in the art, after reading this disclosure, how to make and use alternative embodiments of the present invention in which any number of base stations are associated with any number of wireless switching centers.
[0044] Assistance server 212 comprises hardware and software that is capable of performing the processes described below and in the accompanying figures. In general, assistance server 212 generates GPS assistance data for wireless terminal 201 to aid wireless terminal 201 in acquiring and processing GPS ranging signals from GPS constellation 221. In accordance with the illustrative embodiment, assistance server 212 is a separate physical entity from location server 214; however, it will be clear to those skilled in the art, after reading this disclosure, how to make and use alternative embodiments of the present invention in which assistance server 212 and location server 214 share hardware, software, or both.
[0045] Location client 213 comprises hardware and software that use the estimate of the location of wireless terminal 201 - provided by location server 214 - in a location-based application, as described below and in the accompanying figures.
[0046] Location server 214 comprises hardware and software that generate one or more estimates of the location of wireless terminal 201 as described below and in the accompanying figures. It will be clear to those skilled in the art, after reading this disclosure, how to make and use location server 214. Furthermore, although location server 214 is depicted in Figure 2 as physically distinct from wireless switching center 211, it will be clear to those skilled in the art, after reading this disclosure, how to make and use alternative embodiments of the present invention in which location server 214 is wholly or partially integrated with wireless switching center 211.
[0047] In accordance with the illustrative embodiment, location server 214 communicates with wireless switching center 211, assistance server 212, and location client 213 via a local area network; however it will be clear to those skilled in the art, after reading this disclosure, how to make and use alternative embodiments of the present invention in which location server 214 communicates with one or more of these entities via a different network such as, for example, the Internet, the Public Switched Telephone Network (PSTN), etc.
[0048] In accordance with the illustrative embodiment, wireless switching center 211, assistance server 212, location client 213, and location server 214 are outside of geographic region 220. It will be clear to those skilled in the art, after reading this disclosure, how to make and use alternative embodiments of the present invention in which some or all of wireless switching center 211, assistance server 212, location client 213, and location server 214 are instead within geographic region 220. [0049] Location Server 214 - Figure 3 depicts a block diagram of the salient components of location server 214 in accordance with the illustrative embodiment. Location server 214 comprises: processor 301, memory 302, and local-area network transceiver 303, which are interconnected as shown.
[0050] Processor 301 is a general-purpose processor that is capable of executing operating system 311 and application software 312, and of populating, amending, using, and managing Location-Trait Database 313 and Trait-Correction Database 314, as described in detail below and in the accompanying figures. It will be clear to those skilled in the art how to make and use processor 301.
[0051] Memory 302 is a non-volatile memory that stores: i. operating system 311, and ii. application software 312, and iii. Location-Trait Database 313, and iv. Trait-Correction Database 314. It will be clear to those skilled in the art how to make and use memory 302.
[0052] Transceiver 303 enables location server 214 to transmit and receive information to and from wireless switching center 211, assistance server 212, and location client 213. In addition, transceiver 303 enables location server 214 to transmit information to and receive information from wireless terminal 201 and base stations 202-1 through 202-3 via wireless switching center 211. It will be clear to those skilled in the art how to make and use transceiver 303.
[0053] Operation of the Illustrative Embodiment - Figure 4 depicts a flowchart of the salient processes performed in accordance with the illustrative embodiment of the present invention.
[0054] In accordance with process 401, Location-Trait Database 313 is built. For the purposes of this specification, the "Location-Trait Database" is defined as a database that maps each of a plurality of locations to one or more expected traits associated with a wireless terminal at that location. The details of building Location-Trait Database 313 are described below and in the accompanying figures.
[0055] In accordance with process 402, Trait-Correction Database 314 is built. For the purposes of this specification, the "Trait-Correction Database" is defined as a database that indicates how the measurement of traits can be adjusted to compensate for systemic measurement errors. The details of building Trait-Correction Database 314 are described below and in the accompanying figures. [0056] In accordance with process 403, the location of wireless terminal 201 is estimated based on location-trait database 401, trait-correction database 402, and a variety of traits that vary based on the location of wireless terminal 201. The details of process 403 are described below and in the accompanying figures.
[0057] In accordance with process 404, the estimate of the location of wireless terminal 201 is used in a location-based application, such as and without limitation, E 9- 1-1 service. The details of process 404 are described below and in the accompanying figures.
[0058] In accordance with process 405, Location-Trait Database 313 and Trait- Correction Database 314 are maintained so that their contents are accurate, up-to-date and complete. Process 405 is advantageous because the effectiveness of the illustrative embodiment is based on - and limited by - the accuracy, freshness, and completeness of the contents of Location -Trait Database 313 and Trait-Correction Database 314. The details of process 405 are described below and in the accompanying figures.
[0059] Building Location-Trait Database 313 - Figure 5 depicts a flowchart of the salient processes performed in accordance with process 401 - building Location- Trait Database 313.
[0060] In accordance with process 501, geographic region 220 is partitioned into B(T,N) locations, wherein B(T,N) is a positive integer greater than one, and wherein B(TfN) varies as a function of calendrical time T and the environmental conditions N. It will be clear to those skilled in the art, after reading this disclosure, how to make and use alternative embodiments of the present invention in which the number of locations that geographic region 220 is partitioned into is static. Furthermore, it will be clear to those skilled in the art, after reading this disclosure, how to make and use alternative embodiments of the present invention in which the number of locations that geographic region 220 is partitioned into is not dependent on the calendrical time T or the environmental conditions N.
[O06i] Some traits of the radio frequency spectrum and of individual signals are different at different locations in geographic region 220. Similarly, some traits of the radio frequency spectrum and of individual signals transmitted by wireless terminal 201 change at base stations 202-1, 202-2, and 202-3 when wireless terminal 201 is at different locations. Furthermore, some traits {e.g., hand -off state, etc.) of wireless telecommunications system 200 change when wireless terminal 201 is at different locations. [0062] When wireless terminal 201 is at a particular location, the values of the traits that vary with the location of wireless terminal 201 represent a "fingerprint" or "signature" for that location that enables location server 214 to estimate the location of wireless terminal 201. For example, suppose that under normal conditions the traits have a first set of values when wireless terminal 201 is at a first location, and a second set of values when wireless terminal 201 is at a second location. Then when wireless terminal 201 is at an unknown location and the traits at that unknown location match the second set of values, it is more likely that wireless terminal 201 is at the second location.
[0063] Although human fingerprints and handwritten signatures are generally considered to be absolutely unique, the combination of traits associated with each location might not be absolutely unique in geographic region 220. The effectiveness of the illustrative embodiment is enhanced, however, as differences in the values of the traits among the locations increases. It will be clear to those skilled in the art, after reading this disclosure, how to select locations and traits in order to increase the likelihood that the values of the traits associated with each location are distinguishable from the values of the traits associated with the other locations.
[0064] Each location is described by: i. a unique identifier b, ii. its dimensionality (e.g., one-dimension, two dimensions, three dimensions, four-dimensions, etc.), iii. the coordinates (e.g., latitude, longitude, altitude, etc.) that define its scope (e.g., position, area, volume, etc.), which can be static or, alternatively, can vary as a function of calendrical time T or the environmental conditions Λ/, or both the calendrical time r and the environmental conditions /V. iv. the expected value E(b, T, N, W, Q) for each trait, Q, when wireless terminal W is at location b at calendrical time 7" given environmental conditions, N, v. the identities of its adjacent locations, and vi. the staying and moving probabilities Ps(b, T, N, W) and PM(b, T, N, I/I/, c).
[0065] In accordance with the illustrative embodiment, the identifier of each location is an arbitrarily-chosen positive integer. It will be clear to those skilled in the art, after reading this disclosure, how to make and use alternative embodiments of the present invention in which the identifier of some or all locations is not arbitrarily chosen. Furthermore, it will be clear to those skilled in the art, after reading this disclosure, how to make and use alternative embodiments of the present invention in which the identifier of some or all locations is not a positive integer. [0066] In accordance with the illustrative embodiment, the scope of each location is three-dimensional and is described by (i) one or more three-dimensional coordinates and geometric identifiers that define its boundaries, (ii) a three-dimensional coordinate that resides at the centroid of the location, and (iii) a description of how the scope changes as a function of calendrical time T and environmental conditions /V. It will be clear to those skilled in the art, after reading this disclosure, how to make and use alternative embodiments of the present invention in which the scope of some or all of the locations are one-dimensional or two-dimensional. Furthermore, it will be clear to those skilled in the art, after reading this disclosure, how to make and use alternative embodiments of the present invention in which the scope of some or all of the locations are not a function of calendrical time T or environmental conditions /V.
[0067] In accordance with the illustrative embodiment, the scope of two or more locations can overlap at zero, one, two, more than two, or all points of latitude and longitude (e.g., an overpass and underpass, different stories in a multi-story building as described below, etc.).
[0068] In accordance with the illustrative embodiment, the boundaries of each location are based, at least in part, on: i. natural and man-made physical attributes of geographic region 220 (e.g., buildings, sidewalks, roads, tunnels, bridges, hills, walls, water, cliffs, rivers, etc.), ii. legal laws governing geographic region 220 (e.g., laws that pertain to the location and movement of people and vehicles, etc.), iii. theoretical predictions and empirical data regarding the location and movement of individuals and groups of people and vehicles in geographic region 220, iv. the desired accuracy of the estimates made by location server 214, and v. patterns of the location and movement of people and vehicles within geographic region 220, vi. the calendrical time T1 and vii. the environmental conditions N, subject to the following considerations:
[0069] First, the accuracy with which wireless terminal 201 can be located potentially increases with smaller location sizes. Not all locations need to be the same size, however, and areas requiring greater accuracy can be partitioned into smaller sizes, whereas areas requiring less accuracy can be partitioned into larger sizes. [0070] Second, as the number of locations in geographic region 220 increases, so does the computational burden on location server 214 as described below with respect to Figure 10.
[007i] Third, as the size of adjacent locations decreases, the likelihood increases that the expected values for the traits in those locations will be identical or very similar, which can hinder the ability of location server 214 to correctly determine when wireless terminal 201 is in one location versus the other.
[0072] With these considerations in mind, it will be clear to those skilled in the art, after reading this disclosure, how to make and use alternative embodiments of the present invention that partition geographic region 220 into any number of locations of any size, shape, and arrangement. Furthermore, it will be clear to those skilled in the art, after reading this disclosure, how to make and use embodiments of the present invention in which the locations are identical in size and shape.
[0073] Figure 6a depicts an isometric drawing of geographic region 220 and Figure 6b depicts a map of geographic region 220. Geographic region 220 comprises water fountain 601, park 602, four-story building 603, two-story building 604, various streets, sidewalks, and other features that are partitioned into 28 locations as described below and depicted in Figures 6c through 6e. Although geographic region 220 comprises approximately four square blocks in the illustrative embodiment, it will be clear to those skilled in the art how to make and use alternative embodiments of the present invention with geographic regions of any size, topology, and complexity.
[0074] In accordance with the illustrative embodiment, the eight road intersections are partitioned into Locations 1 through 8, as depicted in Figure 6c. In accordance with the illustrative embodiment, the street sections and their adjacent sidewalks up to the edge of buildings 603 and 604 are partitioned into Locations 9 through 19, as depicted in Figure 6d. In accordance with the illustrative embodiment, water fountain 601 is partitioned into Location 20, park 602 is partitioned into Location 25, each floor of building 604 is classified as one of Locations 21, 22, 23, and 24, and each floor of building 603 is classified as of one of Locations 27 and 28. It will be clear to those skilled in the art, however, after reading this disclosure, how to partition geographic region 220 into any number of locations of any size and shape.
[0075] In accordance with an alternative embodiment of the present invention, a geographic region that comprises a clover-leaf intersection of two, four-lane divided highways is partitioned into 51 locations. Figure 6f depicts an isometric drawing of the intersection, and Figure 6g depicts a map of the intersection. In accordance with the illustrative embodiment, the grass and medians have been partitioned into 15 locations as depicted in Figure 6g, the four ramps have been partitioned into four locations as depicted in Figure 6h, the inner or "passing" lanes have been partitioned into eight locations as depicted in Figure 6i, and the outer or "travel" lanes have been partitioned into eight locations as depicted in Figure 6j.
[0076] Figure 6L depicts an alternative partitioning of geographic region 220 into 64 square locations.
IOO771 In accordance with process 502, the expected values E(b, 7", N, W, Q) for the following traits is associated with each location: i. the expected pathloss of all of the signals receivable by wireless terminal 201 when wireless terminal 201 is at the location, from all transmitters (e.g., base stations 202-1, 202-2, and 202-3, commercial television, commercial radio, navigation, ground-based aviation, etc.), as a function of the calendrical time, T, and the environmental conditions, /V; and ii. the expected pathloss of all of the signals transmitted by wireless terminal 201 when wireless terminal 201 is in the location as receivable at base stations 202-1, 202-2, and 202-3, as a function of the calendrical time, T, and the environmental conditions, N; and iii. the expected received signal strength of all of the signals receivable by wireless terminal 201 when wireless terminal 201 is in the location, from all transmitters, as a function of the calendrical time, T, and the environmental conditions, /V; and iv. the expected received signal strength of all of the signals transmitted by wireless terminal 201 when wireless terminal 201 is in the location as receivable at base stations 202-1, 202-2, and 202-3, as a function of the calendrical time, T, and the environmental conditions, N; and v. the expected received signal-to-impairment ratio (e.g., Eb/No, etc.) of all of the signals receivable by wireless terminal 201 when wireless terminal 201 is in the location, from all transmitters, as a function of the calendrical time, T, and the environmental conditions, N; and vi. the expected received signal-to-impairment ratio of all of the signals transmitted by wireless terminal 201 when wireless terminal 201 is in the location as receivable at base stations 202-1, 202-2, and 202-3, as a function of the calendrical time, T, and the environmental conditions, N; and vii. the expected received temporal difference of each pair of multipath components (e.g., one temporal difference for one pair of multipath components, a pair of temporal differences for a triplet of multipath components, etc.) of all of the signals receivable by wireless terminal 201 when wireless terminal 201 is in the location, from all transmitters, as a function of the calendrical time, T, and the environmental conditions, /V; and viii. the expected received temporal difference of each pair of multipath components (e.g., one temporal difference for one pair of multipath components, a pair of temporal differences for a triplet of multipath components, etc.) of all of the signals transmitted by wireless terminal 201 when wireless terminal 201 is in the location as receivable at base stations 202-1, 202-2, and 202-3, as a function of the calendrical time, T, and the environmental conditions, N; and ix. the expected received delay spread (e.g., RMS delay spread, excess delay spread, mean excess delay spread, etc.) of all of the signals receivable by wireless terminal 201 when wireless terminal 201 is in the location, from all transmitters, as a function of the calendrical time, T, and the environmental conditions, /V; and x. the expected received delay spread (e.g., RMS delay spread, excess delay spread, mean excess delay spread, etc.) of all of the signals transmitted by wireless terminal 201 when wireless terminal 201 is in the location as receivable at base stations 202-1, 202-2, and 202-3, as a function of the calendrical time, T1 and the environmental conditions, /V; and xi. the expected received relative arrival times of two or more multipath components of all of the signals receivable by wireless terminal 201 when wireless terminal 201 is in the location, from all transmitters (which can be determined by a rake receiver in well-known fashion), as a function of the calendrical time, T, and the environmental conditions, N; and xii. the expected received relative arrival times of two or more multipath components of all of the signals transmitted by wireless terminal 201 when wireless terminal 201 is in the location as receivable at base stations 202-1, 202-2, and 202-3, as a function of the calendrical time, T, and the environmental conditions, /V; and xiii. the expected round-trip time of all of the signals transmitted and receivable by wireless terminal 201 through base stations 202-1, 202-2, and 202-3, as a function of the calendrical time, T1 and the environmental conditions, /V; and xiv. the expected round-trip time of all of the signals transmitted and receivable by base stations 202-1, 202-2, and 202-3 through wireless terminal 201, as a function of the calendrical time, T, and the environmental conditions, /V; and xv. the identity of the base stations that provide telecommunications service to the location, as a function of the calendrical time, T1 and the environmental conditions, /V; and xvi. the identities of the neighboring base stations that provide telecommunications service to the location, as a function of the calendrical time, T, and the environmental conditions, /V; and xvii. the handover state (e.g., soft, softer, Ix, 2x, etc.) of wireless terminal
201 and wireless telecommunication system 200 when wireless terminal 201 is in the location as a function of the calendrical time, T1 and the environmental conditions, Λ/.
[0078] In accordance with the illustrative embodiment of the present invention, all signals transmitted by wireless terminal 201 are for communicating with base stations 202-1 through 202-3, and all of the signals received by wireless terminal 201 are:
• signals transmitted by base stations 202-1 through 202-3 for communicating with wireless terminal 201,
• television signals,
• radio signals,
• aviation signals, and
• navigation signals.
It will be clear to those skilled in the art, after reading this disclosure, how to make and use alternative embodiments of the present invention that use different signals.
[0079] In accordance with the illustrative embodiment, the expected values of these traits are determined through a combination of: i. a plurality of theoretical and empirical radio-frequency propagation models, and ii. a plurality of empirical measurements of the traits within geographic region 220, in well-known fashion. The empirical measurements of the traits are stored within location-trait database 313 and updated as described below. [0080] In accordance with the illustrative embodiment of the present invention, each location b is described by the identities of its adjacent locations, (i.e., the locations that wireless terminal 201 can reasonably move into from location b within one time step Δt.) In accordance with the illustrative embodiment, two locations are considered to be "adjacent" when and only when they have at least two points in common. It will be clear to those skilled in the art, however, after reading this disclosure, how to make and use alternative embodiments of the present invention in which two locations are considered adjacent when they have zero points or one point in common.
[0081] Adjacency Graph - In accordance with the illustrative embodiment, a data structure is created that indicates which locations are adjacent. This data structure is called an "adjacency graph" and it is stored within Location-Trait Database 313 in sparse-matrix format. Figure 6m depicts a graphical representation of the adjacency graph for the 28 locations that compose geographic area 220, and Figure 6n depicts a graphical representation of the adjacency graph for the 51 locations that compose the highway intersection in Figures 6f through 6k.
[0082] As described in detail below and in the accompanying figures, the adjacency graph is used in the temporal analysis of wireless terminal 201's movements. It will be clear to those skilled in the art, after reading this disclosure, how to make the adjacency graph for any partitioning of geographic region 220.
[0083] In accordance with the illustrative embodiment, the staying and moving probabilities Psφ, T1. N, W) and PMΦ, T, N, W, C) for all b are generated based on a model of the movement of wireless terminal W that considers: i. the topology of the adjacency graph; and ii. the calendrical time T; and iii. the environmental conditions /V; and iv. the natural and man-made physical attributes that affect the location and movement of wireless terminals and the entities that carry them (e.g., buildings, sidewalks, roads, tunnels, bridges, hills, walls, water, cliffs, rivers, etc.); and v. the legal laws governing the location and movement of wireless terminals and the entities that carry them (e.g., one-way streets, etc.); and vi. the past data for the movement of all wireless terminals; and vii. the past data for the movement of wireless terminal W.
It will be clear to those skilled in the art, after reading this disclosure, how to make and use alternative embodiments of the present invention that use any subcombination of \, ii, iii, iv, v, vi, and vii to generate the staying and moving probabilities for each location b.
[0084] The moving probabilities PMΦ, T, N, W, C) associated with a location b can be considered to be either isotropic or non-isotropic. For the purposes of this specification, "isotropic moving probabilities" are defined as those which reflect a uniform likelihood of direction of movement and "non-isotropic moving probabilities" are defined as those which reflect a non-uniform likelihood of direction of movement. For example, for locations arranged in a two-dimensional regular hexagonal grid the values of PMΦ, T, N, W, c) of location b are isotropic if and only if they are all equal {e.g., PMΦ, T, N, W, c) = 1/6 for each adjacent location c). Conversely, the values of PM(b, T, N, W, c) are non- isotropic if there are at least two probabilities with different values. As another example, for locations arranged in a two-dimensional "checkerboard" grid, the values of PMΦ, T, N, W, c) are isotropic if and only if:
(i) the north, south, east, and west moving probabilities out of location b all equal p,
(ii) the northeast, northwest, southeast, and southwest moving probabilities out of location b all equal p/-v/2 , and
(iii) 4p(l + 1 /V-F) + Psφ, T1 N, W) = 1.
[0085] Isotropic moving probabilities are simple to generate, but are considerably less accurate than non-isotropic moving probabilities that are generated in consideration of the above criteria. Therefore, in accordance with the illustrative embodiment, the moving probabilities are non-isotropic, but it will be clear to those skilled in the art, after reading this disclosure, how to make and use alternative embodiments of the present invention that use isotropic moving probabilities.
[0086] Populating Trait-Correction Database 313 - Figure 7 depicts a flowchart of the salient processes performed as part of process 402: populating Trait- Correction Database 313.
[0087] In general, the ability of location server 214 to estimate the location of wireless terminal 201 is limited by the accuracy with which the traits are measured by wireless terminal 201 and by base stations 202-1, 202-2, and 202-3. When the nature or magnitude of the measurement errors is unpredictably inaccurate, there is little that can be done to overcome them. [0088] In contrast, when the nature and magnitude of the measurement errors are predictable, they can be corrected, and the nature and magnitude of some measurement errors are, in fact, predictable. For example, one make and model of wireless terminal is known to erroneously measure and report the signal strength of signals by -2 dB. If the measurements from this model of wireless terminal are left uπcorrected, this -2 dB error could cause location server 214 to erroneously estimate the location of the wireless terminal. In contrast, if location server 214 adds 2 dB to the measurements from that make and model of wireless terminal, the likelihood that location server 214 would erroneously estimate the location of the wireless terminal would be reduced.
[0089] Trait-Correction Database 313 comprises the information needed by location server 214 to be aware of systemic measurement errors and to correct them. A technique for eliminating some situational errors in the measurements is described below and in the accompanying figures.
[0090] In accordance with process 701, a distortion function is generated for every radio that might provide measurements to location server 214 and for every trait whose measurements can be erroneous.
[0091] In general, the distortion function D(A,K,Q) relates the reported measurement R for a trait Q to the actual value A for that trait and the defining characteristic K of the radio making the measurement:
R = D(A, K1 Q) . (Eq. 1)
[0092] In accordance with the illustrative embodiment, the distortion function D(A,K,Q) is provided to the owner/operator of location server 214 by the radio manufacturer. It will be clear to those skilled in the art, however, after reading this disclosure, how to generate the distortion function D(A,K,Q) for any radio without the assistance of the radio manufacturer.
[0093] An ideal radio perfectly measures and reports the value of the traits it receives and the distortion function D(A,K,Q) for one trait and for an ideal radio is depicted in Figure 8a. As can be seen from the graph in Figure 8a, the salient characteristic of an ideal radio is that the reported value of the measurement, R, is exactly equal to the actual value of the trait /4 at the radio (i.e., there is np. measurement or reporting error).
[0094] In contrast, most real-world radios do not perfectly measure the traits of the signals they receive. This is particularly true for measurements of signal-strength where the errors can be large. For example, Figure 8b depicts a graph of the distortion function of an illustrative real-world radio. In this case, the reported measurement is too high for some values, too low for others, and correct for only one value.
[0095] The nature and magnitude of each of the errors in the reported measurements is inherent in the distortion function D(ArK,Q), and, therefore, knowledge of the distortion function enables the measurement errors to be compensated for. In other words, when location server 214 knows exactly how a radio distorts a measurement, it can correct - or calibrate - the reported measurement with a calibration function to derive the actual value of the trait. The calibration function, denoted C(R,K,Q), is generated in process 1102.
[0096] In accordance with the illustrative embodiment, the distortion function D(A,K,Q) for all measurements is represented in tabular form. For example, the distortion function for one type of signal-strength measurement for various radios is shown in Table 1. It will be clear to those skilled in the art, after reading this disclosure, however, how to make and use alternative embodiments of the present invention in which the distortion function for some or all measurements is not represented in tabular form. Furthermore, it will be clear to those skilled in the art, after reading this disclosure, how to make and use alternative embodiments of the present invention that comprise distortion functions for any type of measurement of any type of trait and for any radio.
Figure imgf000021_0001
Table 1 - The Distortion function D(A,KrQ) in Tabular Form
[0097] The purpose of the characteristic, K, is to identify which calibration function should be used in calibrating the reported measurements from wireless terminal 201, and, therefore, the characteristic, K1 should be as indicative of the actual distortion function for wireless terminal 201 as is economically reasonable.
[0098] For example, the characteristic, K, can be, but is not limited to: i. the unique identity of wireless terminal 201 (e.g., its electronic serial number ("ESN"), its international mobile station identifier ("IMSI"), its temporary international mobile station identifier ("TIMSI"), mobile station identification ("MSID"), its directory number ("DN"), etc.); or ii. the model of wireless terminal 201 {e.g., Timeport 210c, etc.); or iii. the make {i.e., manufacturer) of wireless terminal 201 (e.g., Motorola,
Samsung, Nokia, etc.); or iv. the identity of the radio-frequency circuitry of wireless terminal 201 (e.g.,
Motorola RF circuit design 465B, etc.); or v. the identity of one or more components of wireless terminal 201 (e.g., the part number of the antenna, the part number of the measuring component, etc.); or viii. any combination of i, ii, iii, iv, v, vi, and vii.
[0099] The most accurate characteristic is the unique identity of wireless terminal 201 because that would enable location server 214 to use the calibration function generated for that very wireless terminal. It is unlikely, however, that this is economically feasible because it would require that every wireless terminal be tested to determine its own unique distortion function.
[Oioo] On the other hand, using only the make of wireless terminal 201 as the characteristic, K1 is economically reasonable, but it is unlikely that a single calibration function for all of a manufacturer's wireless terminals would provide very accurate calibrated signal-strength measurements.
[oioi] As a compromise, the illustrative embodiment uses the combination of make and model of wireless terminal 201 as the characteristic, K, because it is believed that the amount of variation between wireless terminals of the same make and model will be small enough that a single calibration function for that model should provide acceptably accurate calibrated measurements for every wireless terminal of that make and model.
[0102] It will be clear to those skilled in the art, however, after reading this disclosure, how to make and use alternative embodiments of the present invention in which the characteristic, K1 is based on something else.
[0103] In accordance with process 502, the calibration function C(R,K,Q) is generated for every radio that might provide measurements to location server 214 and for every trait whose measurements can be distorted. [0104] In general, the calibration function C(R,K,Q) relates the calibrated measurement S of a trait Q1 to the reported measurement R of trait Q and the defining characteristic K of the radio making the measurement:
S = D(R, K, Q) CEq- 2)
[0105] The calibration function C(R,K,Q) is the inverse of the distortion function D(A,K,Q). In other words, the salient characteristic of the calibration function C(R, K1Q) is that it satisfies the equation 3:
S = A ^ C(D(A, K1 Q)1 K, Q) (Eq. 3) so that the calibrated measurement, S, is what the reported measurement, R, would have been had the radio making and reporting the measurement been ideal. It will be clear to those skilled in the art, after reading this disclosure, how to derive C(R,K,Q) from D(A,K,Q). Figure 8c depicts a graph of the calibration function C(R,K,Q) for the distortion function D(A,K,Q) depicted in Figure 8b.
[0106] In accordance with the illustrative embodiment, the function C(R,K,Q) is represented in tabular form, such as that shown in Table 2.
Figure imgf000023_0001
Table 2 - The Calibration Function C(RrC,N) in Tabular Form
[0107] In accordance with process 402, the calibration functions C(R,K,Q) are stored in Trait-Corrections Database 313.
[0108] Maintaining Location-Trait Database 313 - Figure 9 depicts a flowchart of the salient processes performed in process 403: maintaining Location -Trait Database 313 and Trait-Corrections Database 314. The ability of the illustrative embodiment to function is based on - and limited by - the accuracy, freshness, and completeness of the information contained in Location-Trait Database 313 and Trait- Corrections Database 314. [0109] In accordance with process 901, a drive-test regimen is developed that periodically makes empirical measurements throughout geographic region 220 with highly-accurate equipment to ensure the accuracy, freshness, and completeness of the information contained in Location-Trait Database 313 and Trait-Corrections Database 314.
[Olio] In accordance with process 902, the drive-test regimen is implemented.
[Oiii] In accordance with process 903, Location-Trait Database 313 and Trait- Corrections Database 314 are updated, as necessary.
[0ii2] Estimating the Location of Wireless Terminal 201 - Figure 10 depicts a flowchart of the salient processes performed in process 403: estimating the location of wireless terminal 201. In accordance with the illustrative embodiment, process 403 is initiated by a request from location client 213 for the location of wireless terminal 201. It will be clear to those skilled in the art, however, after reading this disclosure, how to make and use alternative embodiments of the present invention in which process 403 is initiated periodically, sporadically, or in response to some other event.
[0113] In accordance with process 1001, Y probability distributions for the location of wireless terminal 201 are generated for each of instants H1 through Hγ in the temporal interval ΔT, wherein Y is a positive integer, based on comparing the measurements of traits associated with wireless terminal 201 at each of instants H1 through Hγ to expected values for those traits at those times. Each of the Y probability distributions provides a first estimate of the probability that wireless terminal 201 is in each location at each of instants H1 through Hy. The details of process 1001 are described below and in the accompanying figures.
[0ii4] In accordance with process 1002, Z probability distributions for the location of wireless terminal 201 are generated for each of instants A1 though Az in the temporal interval ΔT, wherein Z is a positive integer, based on Assisted GPS measurements at wireless terminal 201 at each of instants A1 though Az- Each of the Z probability distributions provides a first estimate of the probability that wireless terminal 201 is in each location at each of instants A1 though Az. The details of process 1002 are described below and in the accompanying figures.
[Oils] In accordance with process 1003, the Y probability distributions generated in process 1001 and the Z probability distributions generated in process 1002 are combined, taking into account their temporal order, to generate a second estimate of the location of wireless terminal 201. The details of process 1003 are described below and in the accompanying figures.
[one] Generating the Probability Distributions for the Location of Wireless Terminal 201 Based on Pattern Matching of Traits - Figure lla depicts a flowchart of the salient processes performed in process 1001 - generating the Y probability distributions for the location of wireless terminal 201 based on comparing the measurements of traits associated with wireless terminal 201 at each of instants H1 through Hγ to expected values for those traits at those times. In accordance with the illustrative embodiment, location server 214 performs each of processes 1101 through 1105 as soon as the data necessary for performing the process becomes available to it.
[0117] In accordance with process 1101, location server 214 receives Y nonempty sets of measurements of the traits, M1 though My, associated with wireless terminal 201. Each set of measurements is made at one of instants H1 through Hγ.
[0118] In accordance with the illustrative embodiment, each set of measurements comprises: i. the pathloss of all of the signals received by wireless terminal 201 from all transmitters {e.g., base stations 202-1, 202-2, and 202-3, commercial television, commercial radio, navigation, ground-based aviation, etc.); and ii. the pathloss of all of the signals transmitted by wireless terminal 201 as received at base stations 202-1, 202-2, and 202-3; and iii. the received signal strength of all of the signals received by wireless terminal 201 from all transmitters; and iv. the received signal strength of all of the signals transmitted by wireless terminal 201 as received at base stations 202-1, 202-2, and 202-3; and v. the received signal-to-impairment ratio of all of the signals received by wireless terminal 201 from all transmitters; and vi. the received signal-to-impairment ratio of all of the signals transmitted by wireless terminal 201 as received at base stations 202-1, 202-2, and 202-3; and vii. the received temporal difference of each pair of multipath components of all of the signals received by wireless terminal 201 from all transmitters; and viii. the received temporal difference of each pair of multipath components of all of the signals transmitted by wireless terminal 201 as received at base stations 202-1, 202-2, and 202-3; and ix. the received delay spread of all of the signals received by wireless terminal 201 from all transmitters; and x. the received delay spread of all of the signals transmitted by wireless terminal 201 as received at base stations 202-1, 202-2, and 202-3; and xi. the received relative arrival times of two or more multipath components of all of the signals received by wireless terminal 201 from all transmitters; and xii. the received relative arrival times of two or more multipath components of all of the signals transmitted by wireless terminal 201 as received at base stations 202-1, 202-2, and 202-3; and xiii. the round-trip time of all of the signals transmitted and received by wireless terminal 201 through base stations 202-1, 202-2, and 202-3; and xiv. the round-trip time of all of the signals transmitted as received at base stations 202-1, 202-2, and 202-3 through wireless terminal 201; and xv. the identity of the base stations that provide telecommunications service to wireless terminal 201; and xvi. the identities of the neighboring base stations that can provide telecommunications service to wireless terminal 201; and xvii. the handover state (e.g., soft, softer, Ix, 2x, etc.) of wireless terminal 201 and wireless telecommunication system 200; and xviii. an indication of the calendrical time, T; and xix. an indication of the environmental conditions, /V.
[0ii9] In accordance with the illustrative embodiment, wireless terminal 201 provides its measurements directly to location server 214 via the user plane and in response to a request from location server 214 to do so. This is advantageous because the quality of the estimate of the location of wireless terminal 201 is enhanced when there are no limitations on the nature, number, or dynamic range of the measurements - as might occur when measurements are required to be made in accordance with the air-interface standard. It will be clear to those skilled in the art, however, after reading this disclosure, how to make and use alternative embodiments of the present invention in which wireless terminal 201 provides its measurements periodically, sporadically, or in response to some other event. Furthermore, it will be clear to those skilled in the art, after reading this disclosure, how to make and use alternative embodiments of the present invention in which wireless terminal 201 provides its measurements to location server 214 via the UMTS protocol.
[0120] In accordance with the illustrative embodiment, base stations 202-1, 202- 2, and 202-3 provide their measurements to location server 214 via wireless switching center 211 and in response to a request from location server 214 to do so. It will be clear to those skilled in the art, however, after reading this disclosure, how to make and use alternative embodiments of the present invention in which base stations 202-1, 202- 2, and 202-3 provide their measurements to location server 214 periodically, sporadically, or in response to some other event.
[0121] As part of process 1101, location server 214 also receives from wireless terminal 201: i. the identities of the base stations that provided service to wireless terminal 201 at each of instants H1 through HYr and ii. the identities of the neighboring base stations that provided service to the location of wireless terminal 201 at each of instants H1 through Hγ. This information is used by location server 214 in performing search area reduction, which is described in detail below.
[0122] In accordance with process 1102, location server 214 uses the calibration functions C(R,K,Q) in the Trait-Corrections Database 314 to correct the systemic errors in the measurements received in process 1001.
[0123] In accordance with process 1103, location server 214 computes the differentials, in those cases that are appropriate, of the measurements to correct the situational errors in the measurements received in process 1001. Many factors, including the condition of wireless terminal 201's antenna, the state of its battery, and whether or not the terminal is inside a vehicle can introduce situational measurement errors. This is particularly true for measurements of pathloss and signal strength.
[0124] The illustrative embodiment ameliorates the effects of these factors by pattern matching not the measurements themselves - whether corrected in process 1102 or not - to the expected values for those traits, but by pattern matching the pair-wise differentials of those measurements to the pair-wise differentials of the expected values for those traits. It will be clear to those skilled in the art, after reading this disclosure, how to make and use alternative embodiments of the present invention in which different measurements are corrected for situational errors by the use of pair- wise differentials.
[0125] A simple example involving signal strengths illustrates this approach. A first radio station, Radio Station A, can be received at -56 dBm at Location 1, -42 dBm at Location 2, -63 dBm at Location 3, and -61 dBm at Location 4, and a second radio station, Radio Station B, can be received at -63 dBm at Location 1, -56 dBm at Location 2, -65 dBm at Location 3, and -52 dBm at Location 4. This information is summarized in the table below and forms the basis for a map or database that correlates location to signal strength.
Figure imgf000028_0001
Table 3 - Illustrative Location-Trait Database (Differential Reception)
[0126] If a given wireless terminal with a broken antenna and at an unknown location receives Radio Station A at -47 dBm and Radio Station B at -61 dBm, then it registers Radio Station A as 14 dBm stronger than Radio Station B. This suggests that the wireless terminal is more likely to be at Location 2 than it is at Location 1, 3, or 4. If the measured signal strengths themselves were pattern matched into Location -Trait Database 313,. the resulting probability distribution for the location of wireless terminal 201 might not be as accurate.
[0127] A disadvantage of this approach is that the situational bias is eliminated at the expense of (1) doubling the variance of the random measurement noise, and (b) reducing the number of data points to pattern match by one. Furthermore, the pair-wise subtraction introduces correlation into the relative signal strength measurement errors (Ae., all of the data points to be matched are statistically correlated). It will be clear to those skilled in the art how to account for this correlation in calculating the likelihood of the measurement report.
[0128] In accordance with process 1104, location server 214 performs a technique called "search area reduction" in preparation for process 1105. To understand what search area reduction is and why it is advantageous, a brief discussion of process 1105 is helpful. In process 1105 location server 214 estimates the probability that wireless terminal 201 is in each location at each of instants H1 through Hγ. This requires generating Y multi-dimensional probability distributions, one for each of instants Hx through Hy.
[0129] The process for generating each multi-dimensional probability distribution can be computationally intensive and the intensity depends on the number of locations that must be considered as possible locations for wireless terminal 201. When the number of locations that must be considered is small, the process can be performed quickly enough for many "real-time" applications. In contrast, when the number of locations that must be considered is large, the process can often take too long.
[0130] Nominally, all of the locations in geographic region 220 must be considered because, prior to process 1104, wireless terminal 201 could be in any location. In accordance with the illustrative embodiment, geographic region 220 comprises only 28 locations. In many alternative embodiments of the present invention, however, geographic region 220 comprises thousands, millions, or billions of locations. The consideration of thousands, millions, or billions of locations for each instant by location server 214 might take too long for many real-time applications.
[0131] Therefore, to expedite the performance of process 1105, location server 214 performs some computationally-efficient tests that quickly and summarily eliminate many possible locations for wireless terminal 201 from consideration, and, therefore, summarily set to zero the probability that wireless terminal 201 is at those locations. This reduces the number of locations that must be fully considered in process 1105 and generally improves the speed with which process 1001 is performed.
[0132] In accordance with search area reduction, for each of instants H1 through Hγ location server 214 uses six computationally efficient tests in an attempt to designate one or more locations as improbable locations for wireless terminal 201. A location that is designated as improbable by one or more of the six tests at instant H1 is designated as improbable by process 1104 at instant H1. To the extent that a location is designated as improbable at instant H1, the computational burden on location server 214 of generating the probability distribution for that instant is reduced.
[0133] There are two types of errors that can be made by process 1104. The first type of error - a Type I error - occurs when process 1104 designates a location as improbable when, in fact, it is not improbable for wireless terminal 201 to be in that location. The second type of error - a Type II error - occurs when process 1104 fails to designate a location as improbable when, in fact, it is improbable that wireless terminal 201 is in that location.
[0134] In general, a Type I error affects the accuracy with which the illustrative embodiment can estimate the location of wireless terminal 201, and a Type II error affects the speed with which processor 1104 can generate the probability distributions. In accordance with the illustrative embodiment, the tests and their parameters are chosen to balance the number of Type I and Type II errors with the computational complexity and value of process 1104. For example, when there are too many Type II errors, the value of process 1104 is undermined by the computational burden of process 1104. It will be clear those skilled in the art, after reading this disclosure, how to make and use alternative embodiments of the present invention that have any number of Type I and Type II errors.
[0135] Figure lib depicts a flowchart of the salient processes performed in accordance with process 1104: search area reduction.
[0136] In accordance with process 1111, location server 214 designates a location as improbable when the difference between a measured value of a trait and the expected value of that trait at that location exceeds a threshold. The theory underlying this test is that a major discrepancy between a measurement of a trait and the expected value of a trait at a location suggests that the measurement was not made when wireless terminal 201 was in that location. In accordance with the illustrative embodiment, location engine 214 performs process 1111 on each measured value of each trait for each signal for each of instants H1 through Hy. It will be clear to those skilled in the art, after reading this disclosure, how to choose the traits and signals and thresholds to achieve the desired number of Type I and Type II errors. It will be clear to those skilled in the art, after reading this disclosure, how to make and use alternative embodiments of the present invention that omit process 1111 or that omit testing one or more traits and/or one or more signals in process 1111.
[0137] In accordance with process 1112, when the magnitude of two measurements of a trait at one instant exceed a first threshold and the magnitude of the expected values for that trait at a location exceed a second threshold, location server 214 designates that location as improbable when a ranking of the two measurements differs from a ranking of the expected values. The theory underlying this test is that a major discrepancy between the ranking of the measurements of a trait and the ranking of the expected values of that trait in the location suggests that the measurements were not made when wireless terminal 201 was in that location. In accordance with the illustrative embodiment, location engine 214 performs process 1112 on each pair of measurements of each trait for each of instants H1 through Hγ. It will be clear to those skilled in the art, after reading this disclosure, how to choose the traits and signals and thresholds to achieve the desired number of Type I and Type II errors. It will be clear to those skilled in the art, after reading this disclosure, how to make and use alternative embodiments of the present invention that omit process 1112 or that omit testing one or more traits and/or one or more signals in process 1112.
[0138] In accordance with process 1113, location server 214 designates a location as improbable when a measurement of traits of a signal is not received when it is expected if wireless terminal 201 were, in fact, in that location. In accordance with the illustrative embodiment, location engine 214 performs process 1113 on each trait of each expected signal for each of instants H1 through Hγ. This test is highly prone to Type I errors and should be used judiciously. It will be clear to those skilled in the art, after reading this disclosure, how to make and use alternative embodiments of the present invention that omit process 1113 or that omit testing one or more traits and/or one or more signals in process 1113.
[0139] In accordance with process 1114, location sever 214 designates a location as improbable when a measurement of a trait of a signal is received when it is not expected if wireless terminal 201 were, in fact, in that location. In accordance with the illustrative embodiment, location engine 214 performs process 1114 on each trait of each signal for each of instants Hi through Hγ. In general, this test is less prone to Type I errors than the test in process 1113. It will be clear to those skilled in the art, after reading this disclosure, how to make and use alternative embodiments of the present invention that omit process 1114 or that omit testing one or more traits and/or one or more signals in process 1114.
[0140] In accordance with process 1115, location server 214 designates a location as improbable when the location is not provided wireless telecommunications service by a base station that is known to be providing service to wireless terminal 201 at that instant. The theory underlying this test is that if a base station that provided telecommunications service to wireless terminal 201 at that instant does not provide service to the location, then it suggests that wireless terminal 201 is not in that location at that instant. In general, this test is highly accurate and has a low number of both Type I and Type II errors. It will be clear to those skilled in the art, after reading this disclosure, how to make and use alternative embodiments of the present invention that omit process 1115.
[Oi4i] In accordance with process 1116, location server 214 designates a location as improbable designating a possible location as improbable when the location is not within the neighboring coverage area of a base station that is known to be a neighboring base station of wireless terminal 201. The theory underlying this test is that if a location is not within the neighboring coverage area of a base station that is a neighbor of wireless terminal 201 at that instant, then it suggests that wireless terminal 201 is not in the location at that instant. In general, this test is highly accurate and has a low number of both Type I and Type II errors. It will be clear to those skilled in the art, after reading this disclosure, how to make and use alternative embodiments of the present invention that omit process 1116. [0142] A location that that is designated as improbable at instant H,- by one or more of processes 1111 through 1116 is designated as improbable by process 1104 at instant H1.
[0143] In accordance with process 1105, location server 214 generates each of the Y probability distribution for that wireless terminal 201 at each of instants H1 through Hγ. To accomplish this, location server 214 performs the processes described below and in Figure lie.
[0144] Figure lie depicts a flowchart of the salient processes performed in accordance with process 1105: generating the Y probability distribution for that wireless terminal 201 at each of instants H1 through HY.
[0145] In accordance with process 1121, location server 214 sets the probability of wireless terminal 201 being at a location at instant H, to zero (0) if the location was designated as improbable at instant H1 by process 1104.
[0146] In accordance with process 1122, location server 214 generates the Euclidean norm between the measurements of a trait and the expected values for that trait at all instants and for all locations not designated as improbable by process 1104. To accomplish this, the EΞuclidean norm is generated between the measurements (as corrected in process 1102, if necessary and/or the differentials of measurements as the case may be) of the expected values for those traits in Lo cation -Trait Database 313. To accomplish this, the Euclidean norm is generated as described in Equation 4:
Vφ.H.) = ^∑((E(b, H1, N, W, Q) - M{b, H1, N, W, Q)) ω(Q)f (Eq. 4) wherein V(b,Hι) is the Euclidean norm for Location b at instant H, based on the square root of the sum of the square of the differences between each (corrected and differential, where appropriate) trait measurement M(b, Hi, N, W, Q) minus the expected value E(b, H1, N, W, Q) for that trait, where ω(Q) is a weighting factor that indicates the relative weight to be given discrepancies in one trait versus discrepancies in the other traits.
[0147] At accordance with process 1123, the un-normalized probabilities of the location of wireless terminal 201 at each location are generated based on the Euclidean norms generated in process 1122 as shown in Equation 5.
- V^b1 H1 ) a*
UP(O1 Hj) = Q (Eq. 5) wherein UP{b,Hj) represents the un-normalized probability that wireless terminal 201 is in Location b at instant H, , and wherein δ% equals:
δ1 = <?J + S* (Eq. 6) wherein S^ \s the square of the uncertainty in the error in Location-Trait Database and S^ is the square of the uncertainty in the calibrated measurements. It will be clear to those skilled in the art, after reading this disclosure, how to generate S2 .
[0148] At process 1124, the probabilities generated in process 1123 are normalized as described in Equation 7.
UPφ, H.) NPCb1 H.) '- — (Eq. 7)
wherein represents the normalized probability that wireless terminal 201 is in Location b.
[0149] As part of process 1124, location server 214 generates a preliminary estimate of the location of wireless terminal 201 at instant H1 based on the maximum likelihood function of the normalized probability distribution at instant H1.
[0150] Generating the Probability Distributions for the Location of Wireless Terminal 201 Based on Assisted GPS - Figure 12 depicts a flowchart of the salient processes performed in process 1002: generating the Z probability distributions for the location of wireless terminal 201 based on GPS-derived information (i.e., information from GPS constellation 221).
[0151] In accordance with processes 1124 and 1201, location server 214 transmits, and assistance server 212 receives, the preliminary estimate of the location of wireless terminal 201 at instant H1 as generated in process 1105.
[0152] In accordance with process 1202, assistance server 212 generates assistance data for wireless terminal 201 based on the preliminary estimate of the location of wireless terminal 201 at instant H1. In accordance with the illustrative embodiment, assistance server 212 generates "fully-custom" assistance data based on the estimate of the location of wireless terminal 201 at instant H1. The assistance data is "fully-custom" because it is specifically tailored to the estimated location of wireless terminal 201 at instant H1, It will be clear to those skilled in the art how to generate fully-custom assistance data for wireless terminal 201 based on the estimated location of wireless terminal 201 at instant H1. As part of process 1202, assistance server 212 transmits the assistance data to wireless terminal 201 via wireless switching center 212 in well-known fashion.
[0153] In accordance with some alternative embodiments of process 1202, assistance server 212 pre-computes assistance data for a plurality of diverse locations within geographic region 220 and selects that pre-computed assistance data for wireless terminal 201 based on the estimated location of wireless terminal 201 at instant H1. Because the assistance data selected for wireless terminal 201 is not specifically tailored to the estimated location of wireless terminal 201 at instant H1, nor generic to all of geographic region 220 or to the cell or sector of the base station serving wireless terminal 201, it is deemed "semi-custom" assistance data. In general, semi-custom assistance data is less accurate than fully-custom assistance data, but more accurate, on average, than generic assistance data, which is chosen based on cell ID alone and that is based on one location within geographic region 220. It will be clear to those skilled in the art, after reading this disclosure, how to generate the fully-custom and semi-custom assistance data for wireless terminal 201.
[0154] In accordance with process 1203, wireless terminal 201 (a) receives the assistance data from assistance server 212, in well-known fashion, (b) uses it to facilitate the acquisition and processing of one or more GPS satellite signals in well- known fashion, and (c) transmits Z non-empty sets of GPS-derived information to location server 214 for readings at instants G1 through GZr where Z is a positive integer. In accordance with the illustrative embodiment of the present invention, each set of GPS-derived information comprises: i. a GPS-derived estimate of the location of wireless terminal 201
{e.g., a latitude, longitude, and altitude coordinate, etc.), or ii. ranging data (e.g., PRN code phase, etc.) from one or more
GPS satellites, or iii. parti a I Iy- processed ranging signals {e.g., signals from which the ranging data has not yet been extracted, etc.) from one or more GPS satellites, or iv. any combination of i, ii, and iii.
[0155] In accordance with process 1204, location server 214 receives Z nonempty sets of GPS-derived information to location server 214 for readings at instants G1 through G2 and generates a probability distribution that indicates the likelihood that wireless terminal 201 is in each location at each of instants G1 through Gz. It will be clear to those skilled in the art how to perform process 1204. [0156] Figure 13 depicts a flowchart of the salient processes performed in process 1003 - combining the Y non-GPS-based probability distributions with the Z GPS- based probability distributions to derive F refined multi-dimensional probability distributions for the location of wireless terminal 201 at each of instants Ji through JF, where each J, corresponds to one of: i. a particular instant HYt where 1 < / ≤ Y, or ii. a particular instant G2, where 1 ≤ z ≤ Z, or iii. a concurrence of both a particular instant Hy, and a particular instant
GZr where 1 ≤ y ≤ Y and 1 ≤ z ≤ Z.
In other words, each "composite" instant J,- corresponds to either an instant associated with a non-GPS-based probability distribution, or an instant associated with a GPS-based probability distribution, or an instant associated with both a non-GPS probability distribution-and a GPS-based probability distribution.
[01S7] In accordance with process 1003, the Y non-GPS-based probability distributions with the Z GPS-based probability distributions are intelligently combined, taking into consideration their relative temporal occurrence to derive a refined multidimensional probability distribution for the location of wireless terminal 201 at instants Ji through JF.
[O158] To generate the refined probability distribution for the location of wireless terminal 201 at instant J1, the probability distributions that occur before instant J, are temporally-extrapolated progressively to instant J1, the probability distributions that occur after instant J1- are temporally-extrapolated regressively to instant J1, and they all are combined with the un-temporally-extrapolated probability distribution for the location of wireless terminal 201 at instant J1. In this way, the accuracy of all of the refined probability distributions for each instant J1 are enhanced by the empirical data at other instants.
[0159] Figure 14 depicts a first example of determining each of instants J1 through JF based on non-GPS-based instants H1 through HYr where V=4, and GPS-based instants Gi through GZr where Z=6. As can be seen in Figure 14, the number of composite instants F is at most Y plus Z, and is at least the maximum of Y and Z - the former occurring when there are no coincident GPS/non-GPS probability distributions, and the latter when there are as many as possible coincident GPS/non-GPS probability distributions.
[0160] Figure 15 depicts a second example of determining each of instants Ji through JF based on non-GPS-based instants and GPS-based instants. This second example illustrates that even when the non-GPS-based instants are uniformly spaced in time and the GPS-based instants are uniformly spaced in time, the composite instants are no_t necessarily uniformly spaced in time.
[0161] In accordance with the present invention, the time step Δt is defined as the minimum time interval between any two instants. The time step is atomic in that the time difference between any two instants is an integral multiple of time steps. (Note that two consecutive instants - whether they are non-GPS-based instants, GPS-based instants, or composite instants - might be more than a single time step apart.) The time step of the present invention is therefore similar to the time step employed in clock- driven discrete event simulations.
[0162] As will be appreciated by those skilled in the art, selecting an appropriate value for the time step Δt typically will depend on the particular application, and involves a tradeoff between (1) temporal precision and (2) available memory and processing power. As will be further appreciated by those skilled in the art, after reading this disclosure, the selected time step can affect the definition of locations, the moving and staying probabilities, and consequently the graphs that are derived from them {e.g., the adjacency graph, etc.).
[0163] In accordance with process 1301, location server 214 determines instants J1 through JF, as described above.
[0164] In accordance with process 1302, location server 214 constructs unrefined probability distributions V1 through VF for instants Ji through JF as follows: i. if J1 corresponds to a particular Hj only, then V1 equals the non-GPS probability distribution at instant Hj, ii. if J/ corresponds to a particular G^ only, then Vi equals the GPS probability distribution at instant Gk, and iii. otherwise (C,- corresponds to both a particular Hj and a particular Gk), Vi equals a probability distribution that equals the normalized product of the non-GPS and GPS probability distributions at instant J1.
[0165] In accordance with process 1303, location server 214 determines for each instant J1-, temporally-extrapolated probability distributions Dy for aU j'Φi, 1 ≤ j ≤ F, which are based on (i) the unrefined probability distribution Vj at instant Jj, (ii) Ps(b, T, N, W)1 and (iii)
Figure imgf000036_0001
T, N, W, C). The extrapolated probability distribution D,rj is therefore a predictive probability distribution at instant J,- that is based on empirical data at instant Jj - but not on any empirical data at other instants, including J1. i. the past data for the movement of all wireless terminals; and ii. the past data for the movement of wireless terminal W; and iii. the location, speed, and acceleration of wireless terminal W at calendrical time 7"; and iv. the state of traffic signals that can affect the movement of wireless terminals in location b.
[0166] A temporally-extrapolated probability distribution can be progressed {i.e., projected into the future based on a past probability distribution). For example, if instant J3 is one time step after instant Jz, then extrapolated probability distribution D3,2 is derived by a single application of Ps(b, T, Nr W) and PM(b, T, N, W, c) to unrefined probability distribution V2. In other words, for any location b:
D3ι2{b1 ÷ V2[b]- . Psφ, J2, N1 W) + ∑V2[c] . PM(c, J2, N, W, b) (Eq. 8)
(c,b)ein(b) where in(b) is the set of arcs into location b from other locations in the adjacency graph. Similarly, a temporally-extrapolated probability distribution can be regressed (i.e., projected into the past based on a future unrefined probability distribution) based on the equation:
V3Ib ] = D2/3[6] - Psφ, J21N1W) + ∑D2r3\c\- . PM(c,J2l N,W,b) (Eq. 9)
(c,_))ε/π(£>) by setting up a system of equations (9) for a plurality of locations {&l 5δ2,...,^}and solving for (D23[^1 ], D2 3[b2], ..., D23 [bη]} via matrix algebra.
[0167] As will be well-understood by those skilled in the art, after reading this disclosure, when consecutive instants are two or more time steps apart, then Equation 8 can be applied iteratively in well-known fashion. (Because the time step is atomic the number of iterations is always integral.) As will be further appreciated by those skilled in the art, after reading this disclosure, the extrapolated probability distributions for non- consecutive time instants (e.g., D2,4, Ds1I1 etc.) can be efficiently computed in a bottom- up fashion from the extrapolated probability distributions for consecutive time instants via dynamic programming.
[0168] In accordance with process 1304, location server 214 computes each refined probability distribution L/, corresponding to each instant J/, 1 < / < F, as a weighted average of: i. the corresponding unrefined probability distribution Vn and ii. all available temporally-extrapolated probability distributions Dy, j≠i : V1 + ∑[«"-" - 0,fj,] L = ^ (Eq. 10) i + 2>"-'i j≠l wherein α is a constant, 0 < α < 1, that acts as an "aging factor" that weights less temporally-extrapolated probability distributions more heavily that more temporally- extrapolated probability distributions because of the more temporally-extrapolated probabilities distributions are less likely to be correct than the less temporally- extrapolated probability distributions. For example, when /=4 and F=5, Equation 10 in expanded form yields:
V4 + a - D4 3 + OC - D4 5 + a2 ■ D4 2 + a3 - D4 1
L4 = : — - ~ - (Eq. 11)
1 + 2a + a + a
[0169] Defining D1/, = Vh Equation 10 can be expressed in a simpler form that is particularly convenient for computer processing :
L1 = ^-7= (Eq. 12)
∑«»-'»
[0170] In accordance with process 1305, location server 214 generates an estimate of the location of wireless terminal 201 at one or more instants J,- based on the maximum likelihood function of L1. (As will be appreciated by those skilled in the art, after reading this disclosure, in some other embodiments of the present invention an estimate might be generated from probability distribution L1 using another function or method.)
[Oi7i] In accordance with process 1306, location server 214 provides the estimate(s) of the location of wireless terminal 201 generated in process 1305 to location client 213, in well-known fashion.
[0172] It is to be understood that the above -described embodiments are merely illustrative of the present invention and that many variations of the above-described embodiments can be devised by those skilled in the art without departing from the scope of the invention. It is therefore intended that such variations be included within the scope of the following claims and their equivalents.

Claims

What is claimed is:
1. A process comprising: generating a first non-GPS-derived estimate of the location of a wireless terminal based on a first measurement of a trait of a first signal; and generating assistance data for a satellite signal that is received by said wireless terminal, wherein said assistance data is based on said first non-GPS-derived estimate of the location of said wireless terminal.
2. The process of claim 1 further comprising receiving a second estimate of the location of said wireless terminal from said wireless terminal based on said satellite signal.
3. The process of claim 2 further comprising generating a third estimate of the location of said wireless terminal based on said first measurement and said second estimate of the location of said wireless terminal.
4. The process of claim 2 further comprising generating a third estimate of the location of said wireless terminal based on said second estimate of the location of said wireless terminal and a second measurement of said trait of said first signal.
5. The process of claim 1 further comprising receiving ranging data from said wireless terminal based on said satellite signal; and generating a second estimate of the location of said wireless terminal based on said ranging data.
6. The process of claim 1 further comprising receiving ranging data from said wireless terminal based on said satellite signal; and generating a second estimate of the location of said wireless terminal based on said ranging data and said first measurement.
7. The process of claim 1 further comprising receiving ranging data from said wireless terminal based on said satellite signal; and generating a second estimate of the location of said wireless terminal based on said ranging data and a second measurement of said trait of said first signal.
8. The process of claim 1 further comprising receiving a partial Iy- processed satellite signal from said wireless terminal based on said satellite signal; and generating a second estimate of the location of said wireless terminal based on said partially-processed satellite signal.
9. The process of claim 1 further comprising receiving a partially-processed satellite signal from said wireless terminal based on said satellite signal; and generating a second estimate of the location of said wireless terminal based on said partial Iy- processed satellite signal and said first measurement.
10. The process of claim 1 further comprising receiving a partially-processed satellite signal from said wireless terminal based on said satellite signal; and generating a second estimate of the location of said wireless terminal based on said partially-processed satellite signal and a second measurement of said trait of said first signal.
11. The process of claim 1 wherein said assistance data is fully-custom based on said first non-GPS-derived estimate of the location of said wireless terminal.
12. The process of claim 1 wherein said assistance data is semi-custom based on said first non-GPS-derived estimate of the location of said wireless terminal.
13. A process comprising: generating a first non-GPS-derived estimate of the location of a wireless terminal that is more accurate than an estimate based on cell ID alone; and generating assistance data for a satellite signal that is received by said wireless terminal, wherein said assistance data is based on said first non-GPS-derived estimate.
14. The process of claim 13 further comprising receiving a second estimate of the location of said wireless terminal from said wireless terminal based on said satellite signal.
15. The process of claim 14 further comprising generating a third estimate of the location of said wireless terminal based on said second estimate of the location of said wireless terminal and said first non-GPS-derived estimate.
16. The process of claim 14 further comprising generating a third estimate of the location of said wireless terminal based on said second estimate of the location of said wireless terminal and an measurement of a trait of a first signal.
17. The process of claim 13 further comprising receiving ranging data from said wireless terminal based on said satellite signal; and generating a second estimate of the location of said wireless terminal based on said ranging data.
18. The process of claim 17 further comprising receiving ranging data from said wireless terminal based on said satellite signal; and generating a second estimate of the location of said wireless terminal based on said ranging data and said first non-GPS-derived estimate.
19. The process of claim 17 further comprising receiving ranging data from said wireless terminal based on said satellite signal; and generating a second estimate of the location of said wireless terminal based on said ranging data and an measurement of a trait of a first signal.
20. The process of claim 13 further comprising receiving a partially-processed satellite signal from said wireless terminal based on said satellite signal; and generating a second estimate of the location of said wireless terminal based on said partially-processed satellite signal.
21. The process of claim 13 further comprising receiving a partially-processed satellite signal from said wireless terminal based on said satellite signal; and generating a second estimate of the location of said wireless terminal based on said partially-processed satellite signal and said first non-GPS-derived estimate.
22. The process of claim 13 further comprising receiving partially-processed satellite signal from said wireless terminal based on said satellite signal; and generating a second estimate of the location of said wireless terminal based on said partially-processed satellite signal and an measurement of a trait of a first signal.
23. The process of claim 13 wherein said assistance data is fully-custom based on said first non-GPS-derived estimate of the location of said wireless terminal.
24. The process of claim 13 wherein said assistance data is semi-custom based on said first non-GPS-derived estimate of the location of said wireless terminal.
25. A process comprising: generating a first non-G PS-derived estimate of the location of a wireless terminal based on comparing a first measurement of a trait of a first signal to a map that correlates locations with predicted values of said trait; and generating assistance data for a satellite signal that is received by said wireless terminal, wherein said assistance data is based on said first non-GPS-derived estimate of the location of said wireless terminal.
26. The process of claim 25 further comprising receiving a second estimate of the location of said wireless terminal from said wireless terminal based on said satellite signal.
27. The process of claim 26 further comprising generating a third estimate of the location of said wireless terminal based on said first measurement and said second estimate of the location of said wireless terminal.
28. The process of claim 26 further comprising generating a third estimate of the location of said wireless terminal based on said second estimate of the location of said wireless terminal and a second measurement of said trait of said first signal.
29. The process of claim 25 further comprising receiving ranging data from said wireless terminal based on said satellite signal; and generating a second estimate of the location of said wireless terminal based on said ranging data.
30. The process of claim 25 further comprising receiving ranging data from said wireless terminal based on said satellite signal; and generating a second estimate of the location of said wireless terminal based on said ranging data and said first measurement.
31. The process of claim 25 further comprising receiving ranging data from said wireless terminal based on said satellite signal; and generating a second estimate of the location of said wireless terminal based on said ranging data and a second measurement of said trait of said first signal.
32. The process of claim 25 further comprising receiving a partially-processed satellite signal from said wireless terminal based on said satellite signal; and generating a second estimate of the location of said wireless terminal based on said partially-processed satellite signal.
33. The process of claim 25 further comprising receiving a partially-processed satellite signal from said wireless terminal based on said satellite signal; and generating a second estimate of the location of said wireless terminal based on said partially-processed satellite signal and said first measurement.
34. The process of claim 25 further comprising receiving a partially-processed satellite signal from said wireless terminal based on said satellite signal; and generating a second estimate of the location of said wireless terminal based on said partially-processed satellite signal and a second measurement of said trait of said first signal.
35. The process of claim 25 wherein said assistance data is fully-custom based on said first non-GPS-derived estimate of the location of said wireless terminal.
36. The process of claim 25 wherein said assistance data is semi-custom based on said first non-GPS-derived estimate of the location of said wireless terminal.
37. A process comprising: generating a first assistance data for a satellite signal at a first location that is serviced by a base station; generating a second assistance data for said satellite signal at a second location that is serviced by said base station; generating a first non-GPS-derived estimate of the location of a wireless terminal that is serviced by said base station; and transmitting said first assistance data to said wireless terminal when said first non-GPS-derived estimate of the location of said wireless terminal is closer to said first location than said second location, and transmitting said second assistance data to said wireless terminal when said first non-GPS-derived estimate of the location of said wireless terminal is closer to said second location than said first location
38. The process of claim 37 wherein said first non-GPS-derived estimate of the location of said wireless terminal is based on a first measurement of a trait of a first signal.
39. The process of claim 37 wherein said first non-GPS-derived estimate of the location of said wireless terminal that is more accurate than an estimate based on cell ID alone.
40. The process of claim 37 wherein said first non-GPS-derϊved estimate of the location of said wireless terminal is based on comparing a first measurement of a trait of a first signal to a map that correlates locations with predicted values of said trait.
41. The process of claim 37 further comprising receiving a second estimate of the location of said wireless terminal from said wireless terminal based on said satellite signal.
42. The process of claim 41 further comprising generating a third estimate of the location of said wireless terminal based on said first measurement and said second estimate of the location of said wireless terminal.
43. The process of claim 41 further comprising generating a third estimate of the location of said wireless terminal based on said second estimate of the location of said wireless terminal and a second measurement of said trait of said first signal.
44. The process of claim 37 further comprising receiving ranging data from said wireless terminal based on said satellite signal; and generating a second estimate of the location of said wireless terminal based on said ranging data.
45. The process of claim 37 further comprising receiving ranging data from said wireless terminal based on said satellite signal; and generating a second estimate of the location of said wireless terminal based on said ranging data and said first measurement.
46. The process of claim 37 further comprising receiving ranging data from said wireless terminal based on said satellite signal; and generating a second estimate of the location of said wireless terminal based on said ranging data and a second measurement of said trait of said first signal.
47. The process of claim 37 further comprising receiving a partially-processed satellite signal from said wireless terminal based on said satellite signal; and generating a second estimate of the location of said wireless terminal based on said partially-processed satellite signal.
48. The process of claim 37 further comprising receiving a partially-processed satellite signal from said wireless terminal based on said satellite signal; and generating a second estimate of the location of said wireless terminal based on said partial Iy- processed satellite signal and said first measurement.
49. The process of claim 37 further comprising receiving a partially-processed satellite signal from said wireless terminal based on said satellite signal; and generating a second estimate of the location of said wireless terminal based on said partially-processed satellite signal and a second measurement of said trait of said first signal.
PCT/US2007/062010 2006-05-22 2007-02-12 Estimating the location of a wireless terminal based on assisted gps and pattern matching WO2007136897A1 (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
EP07756889A EP2027483A1 (en) 2006-05-22 2007-02-12 Estimating the location of a wireless terminal based on assisted gps and pattern matching

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
US11/419,640 2006-05-22
US11/419,640 US8965393B2 (en) 2006-05-22 2006-05-22 Estimating the location of a wireless terminal based on assisted GPS and pattern matching

Publications (1)

Publication Number Publication Date
WO2007136897A1 true WO2007136897A1 (en) 2007-11-29

Family

ID=37187598

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/US2007/062010 WO2007136897A1 (en) 2006-05-22 2007-02-12 Estimating the location of a wireless terminal based on assisted gps and pattern matching

Country Status (4)

Country Link
US (2) US8965393B2 (en)
EP (1) EP2027483A1 (en)
JP (1) JP2007316067A (en)
WO (1) WO2007136897A1 (en)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109959894A (en) * 2017-12-26 2019-07-02 深圳市优必选科技有限公司 Localization method and terminal device

Families Citing this family (60)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7899467B2 (en) * 1998-09-22 2011-03-01 Polaris Wireless, Inc. Estimating the location of a wireless terminal based on the traits of the multipath components of a signal
US10687166B2 (en) 2004-09-30 2020-06-16 Uber Technologies, Inc. Obtaining user assistance
US10445799B2 (en) 2004-09-30 2019-10-15 Uber Technologies, Inc. Supply-chain side assistance
US8358976B2 (en) 2006-03-24 2013-01-22 The Invention Science Fund I, Llc Wireless device with an aggregate user interface for controlling other devices
JP2007316070A (en) * 2006-05-22 2007-12-06 Polaris Wireless Inc Method for predicting position of wireless terminal
JP2007316068A (en) * 2006-05-22 2007-12-06 Polaris Wireless Inc Method of estimating location of wireless terminal
US9083745B2 (en) * 2007-03-12 2015-07-14 Qualcomm Incorporated Network independent location services
US9078227B2 (en) * 2007-06-14 2015-07-07 Intel Corporation Location support in wireless networks
US8483706B2 (en) * 2008-04-15 2013-07-09 Qualcomm Incorporated Location services based on positioned wireless measurement reports
GB2460626A (en) * 2008-05-22 2009-12-09 Geotate Bv File creation system and method
US8838132B2 (en) * 2009-08-12 2014-09-16 Qualcomm Incorporated Enhanced positioning assistance data for reduced signaling
WO2011027347A2 (en) * 2009-09-02 2011-03-10 Pin Nav Llc Device and method for calculating time of arrival of a frame in a wireless network
US8903940B2 (en) * 2009-09-10 2014-12-02 Tribal Technologies, Inc. System and method for intelligently distributing content to a mobile device based on a detected location of the mobile device and context data defining characteristics of the location at a particular date and time
US8558693B2 (en) * 2009-09-10 2013-10-15 Tribal Technologies, Inc. System and method for location-based reminders on a mobile device
US9131459B2 (en) * 2010-02-01 2015-09-08 Qualcomm Incorporated Mobile station positioning assistance with local mapping data
US9196157B2 (en) 2010-02-25 2015-11-24 AT&T Mobolity II LLC Transportation analytics employing timed fingerprint location information
US9053513B2 (en) 2010-02-25 2015-06-09 At&T Mobility Ii Llc Fraud analysis for a location aware transaction
US9008684B2 (en) 2010-02-25 2015-04-14 At&T Mobility Ii Llc Sharing timed fingerprint location information
KR101429953B1 (en) * 2010-04-02 2014-08-13 에스케이텔레콤 주식회사 Method and Apparatus for Updating Database for pCell Positioning
US9414269B2 (en) * 2010-05-14 2016-08-09 Blackberry Limited Systems and methods of transmitting measurement reports
US8938115B2 (en) 2010-11-29 2015-01-20 The Regents Of The University Of California Systems and methods for data fusion mapping estimation
US9009629B2 (en) 2010-12-01 2015-04-14 At&T Mobility Ii Llc Motion-based user interface feature subsets
US8781496B2 (en) * 2011-01-19 2014-07-15 Qualcomm Incorporated Methods and apparatus for mobile device location determination
KR20120092925A (en) * 2011-02-14 2012-08-22 삼성전자주식회사 Device and method for measuring and reporting a mdt information of mobile terminal
US8903414B2 (en) * 2011-06-03 2014-12-02 Apple Inc. Location estimation using a probability density function
US9462497B2 (en) 2011-07-01 2016-10-04 At&T Mobility Ii Llc Subscriber data analysis and graphical rendering
US9519043B2 (en) 2011-07-21 2016-12-13 At&T Mobility Ii Llc Estimating network based locating error in wireless networks
US8897802B2 (en) 2011-07-21 2014-11-25 At&T Mobility Ii Llc Selection of a radio access technology resource based on radio access technology resource historical information
EP2752049B1 (en) * 2011-09-19 2015-11-18 Telefonaktiebolaget L M Ericsson (publ) Data transfer in mobile networks
US8909247B2 (en) 2011-11-08 2014-12-09 At&T Mobility Ii Llc Location based sharing of a network access credential
US9026133B2 (en) 2011-11-28 2015-05-05 At&T Mobility Ii Llc Handset agent calibration for timing based locating systems
US8970432B2 (en) 2011-11-28 2015-03-03 At&T Mobility Ii Llc Femtocell calibration for timing based locating systems
US8925104B2 (en) 2012-04-13 2014-12-30 At&T Mobility Ii Llc Event driven permissive sharing of information
US8532676B1 (en) * 2012-05-22 2013-09-10 Polaris Wireless, Inc. Estimating whether a wireless terminal is indoors versus outdoors using probabilities and classifications
US9094929B2 (en) 2012-06-12 2015-07-28 At&T Mobility Ii Llc Event tagging for mobile networks
US9326263B2 (en) 2012-06-13 2016-04-26 At&T Mobility Ii Llc Site location determination using crowd sourced propagation delay and location data
US8938258B2 (en) 2012-06-14 2015-01-20 At&T Mobility Ii Llc Reference based location information for a wireless network
US8897805B2 (en) 2012-06-15 2014-11-25 At&T Intellectual Property I, L.P. Geographic redundancy determination for time based location information in a wireless radio network
US9408174B2 (en) 2012-06-19 2016-08-02 At&T Mobility Ii Llc Facilitation of timed fingerprint mobile device locating
US8892054B2 (en) 2012-07-17 2014-11-18 At&T Mobility Ii Llc Facilitation of delay error correction in timing-based location systems
US9351223B2 (en) 2012-07-25 2016-05-24 At&T Mobility Ii Llc Assignment of hierarchical cell structures employing geolocation techniques
US8838137B2 (en) 2012-08-30 2014-09-16 Polaris Wireless, Inc. Estimating the location of a wireless terminal in wireless telecommunications systems that comprise distributed and/or repeater antennas
US9408178B2 (en) 2013-01-22 2016-08-02 Apple Inc. Detecting mobile access points
EP2973245A4 (en) 2013-03-15 2017-01-11 Factual Inc. Crowdsouorcing domain specific intelligence
CN103327605B (en) * 2013-05-31 2015-12-23 武汉理工大学 Based on the radio frequency positioning method of token ring and system under environment of internet of things
US9400321B2 (en) 2013-06-05 2016-07-26 Apple Inc. Utilizing mobile wireless access gateways for location and context purposes
US9250087B2 (en) * 2014-02-26 2016-02-02 International Business Machines Corporation Identification of mobile device location
WO2015162458A1 (en) 2014-04-24 2015-10-29 Singapore Telecommunications Limited Knowledge model for personalization and location services
US9552559B2 (en) 2014-05-06 2017-01-24 Elwha Llc System and methods for verifying that one or more directives that direct transport of a second end user does not conflict with one or more obligations to transport a first end user
US9791572B2 (en) 2014-05-16 2017-10-17 Apple Inc. Batch processing for improved georeferencing
EP3227708A1 (en) * 2014-12-04 2017-10-11 HERE Global B.V. Supporting a collaborative collection of data
US9351111B1 (en) 2015-03-06 2016-05-24 At&T Mobility Ii Llc Access to mobile location related information
US10108728B2 (en) 2015-08-22 2018-10-23 Microsoft Technology Licensing, Llc Provision of location information with search queries from location unaware devices to increase user interaction performance
KR102612792B1 (en) * 2016-10-28 2023-12-13 삼성전자주식회사 Electronic device and method for determining entry in region of interest thereof
AU2016433153B2 (en) * 2016-12-23 2022-03-31 Dataspark Pte, Ltd Estimated user location from cellular telephony data
AU2017399008A1 (en) 2017-02-17 2019-09-05 Dataspark Pte, Ltd Mobility gene for visit data
AU2017399007B2 (en) 2017-02-17 2021-12-23 Dataspark Pte, Ltd Mobility gene for trajectory data
US20210172759A1 (en) 2017-02-17 2021-06-10 Dataspark Pte Ltd Map Matching and Trajectory Analysis
US11722842B2 (en) 2017-12-18 2023-08-08 Sony Corporation Telecommunications apparatus and methods
US10516972B1 (en) 2018-06-01 2019-12-24 At&T Intellectual Property I, L.P. Employing an alternate identifier for subscription access to mobile location information

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20040152470A1 (en) * 2003-02-04 2004-08-05 Spain David Stevenson Location estimation of wireless terminals though pattern matching of signal-strength differentials
US20040198386A1 (en) * 2002-01-16 2004-10-07 Dupray Dennis J. Applications for a wireless location gateway
US20050148346A1 (en) * 2003-12-30 2005-07-07 Maloney John E. TDOA/GPS hybrid wireless location system

Family Cites Families (49)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5293642A (en) * 1990-12-19 1994-03-08 Northern Telecom Limited Method of locating a mobile station
US5404376A (en) * 1993-09-09 1995-04-04 Ericsson-Ge Mobile Communications Inc. Navigation assistance for call handling in mobile telephone systems
US5717406A (en) * 1995-06-07 1998-02-10 Sanconix Inc. Enhanced position calculation
JP3231787B2 (en) * 1996-03-05 2001-11-26 松下電器産業株式会社 Location information detection system
GB2311697B (en) * 1996-03-22 1999-07-28 Matsushita Electric Ind Co Ltd Wireless communication system and method and system for detection of position of radio mobile station
JP3161334B2 (en) 1996-07-29 2001-04-25 松下電器産業株式会社 Position detection device
US6249252B1 (en) * 1996-09-09 2001-06-19 Tracbeam Llc Wireless location using multiple location estimators
US6236365B1 (en) * 1996-09-09 2001-05-22 Tracbeam, Llc Location of a mobile station using a plurality of commercial wireless infrastructures
FI104528B (en) 1996-10-03 2000-02-15 Nokia Networks Oy Procedure for locating a mobile station, and cellular radio network
US6064339A (en) * 1997-01-08 2000-05-16 Us Wireless Corporation Subspace signature matching for location ambiguity resolution in wireless communication systems
US6026304A (en) * 1997-01-08 2000-02-15 U.S. Wireless Corporation Radio transmitter location finding for wireless communication network services and management
US6195556B1 (en) * 1997-07-15 2001-02-27 Metawave Communications Corporation System and method of determining a mobile station's position using directable beams
US6496701B1 (en) * 1998-08-25 2002-12-17 Lucent Technologies Inc. Pattern-recognition-based geolocation
US6944465B2 (en) * 1998-09-22 2005-09-13 Polaris Wireless, Inc. Estimating the location of a mobile unit based on the elimination of improbable locations
US6393294B1 (en) * 1998-09-22 2002-05-21 Polaris Wireless, Inc. Location determination using RF fingerprinting
US6782262B1 (en) * 1998-10-28 2004-08-24 Telefonaktiebolaget Lm Ericsson Self-tuning sufficient signal strength threshold
JP2000137066A (en) 1998-10-30 2000-05-16 Matsushita Electric Works Ltd Gps receiving device
AU1318300A (en) 1998-12-04 2000-06-26 U.S. Wireless Corporation Wireless location determination using spatial signature information
US6850764B1 (en) * 1998-12-17 2005-02-01 Cisco Technology, Inc. Method and system for allocating bandwidth in a wireless communications network
US6799047B1 (en) * 1999-02-25 2004-09-28 Microsoft Corporation Locating and tracking a user in a wireless network through environmentally profiled data
US6564065B1 (en) * 1999-04-20 2003-05-13 Lucent Technologies Inc. Bayesian-update based location prediction method for CDMA systems
US6411892B1 (en) * 2000-07-13 2002-06-25 Global Locate, Inc. Method and apparatus for locating mobile receivers using a wide area reference network for propagating ephemeris
US6263208B1 (en) * 1999-05-28 2001-07-17 Lucent Technologies Inc. Geolocation estimation method for CDMA terminals based on pilot strength measurements
GB9915277D0 (en) 1999-07-01 1999-09-01 Aircom International Limited Mobile telephone positioning system
GB0014719D0 (en) * 2000-06-16 2000-08-09 Koninkl Philips Electronics Nv A method of providing an estimate of a location
US6658258B1 (en) * 2000-09-29 2003-12-02 Lucent Technologies Inc. Method and apparatus for estimating the location of a mobile terminal
US7003288B2 (en) * 2000-10-11 2006-02-21 Mitsubishi Denki Kabushiki Kaisha Mobile communication terminal
KR100460274B1 (en) * 2001-08-11 2004-12-04 (주)넷피아닷컴 System for providing informations related a location using keyword name and method thereof
WO2003021851A2 (en) 2001-09-05 2003-03-13 Newbury Networks, Inc. Position detection and location tracking in a wireless network
JP4759892B2 (en) * 2001-09-14 2011-08-31 日本電気株式会社 Mobile phone terminal and control method
US6873852B2 (en) * 2002-01-10 2005-03-29 Telefonaktiebolaget Lm Ericsson (Publ) System and method of estimating the position of a mobile terminal in a radio telecommunications network
US6975939B2 (en) * 2002-07-29 2005-12-13 The United States Of America As Represented By The Secretary Of The Army Mapping patterns of movement based on the aggregation of spatial information contained in wireless transmissions
US7433695B2 (en) * 2002-11-18 2008-10-07 Polaris Wireless, Inc. Computationally-efficient estimation of the location of a wireless terminal based on pattern matching
US7242950B2 (en) * 2003-02-18 2007-07-10 Sbc Properties, L.P. Location determination using historical data
US8971913B2 (en) * 2003-06-27 2015-03-03 Qualcomm Incorporated Method and apparatus for wireless network hybrid positioning
US7250907B2 (en) * 2003-06-30 2007-07-31 Microsoft Corporation System and methods for determining the location dynamics of a portable computing device
CA2533145C (en) 2003-07-23 2013-04-09 Qualcomm Incorporated Selecting a navigation solution used in determining the position of a device in a wireless communication system
US7460871B2 (en) * 2004-01-16 2008-12-02 Skyguard, Llc Method and system for tracking mobile telemetry devices
GB0410609D0 (en) * 2004-05-12 2004-06-16 Nokia Corp Locating mobile terminals
US20060009236A1 (en) * 2004-06-09 2006-01-12 Vanu Bose Determining a location
JP2006038732A (en) 2004-07-29 2006-02-09 Seiko Epson Corp Information providing system, information providing device, control method for information providing device, control program for information providing device, computer-readable recording medium stored with control program on information providing device, and terminal device
JP2006047219A (en) 2004-08-06 2006-02-16 Seiko Epson Corp Information-providing system, information-providing device, control method of information providing device, control program of the information-providing device, and computer-readable with medium recording control program of the information providing device stored
JP2006047233A (en) 2004-08-09 2006-02-16 Seiko Epson Corp Positioning system, intermediation device, control method for the intermediation device, control program for the intermediation device, and computer-readable recording medium stored with control program for the intermediation device
US7256733B2 (en) 2004-10-21 2007-08-14 Qualcomm Incorporated Method and system for positioning signal acquisition assistance window evaluation
JP2006126129A (en) 2004-11-01 2006-05-18 Seiko Epson Corp Positioning device, positioning method, control program of positioning device, and recording medium readable by computer for recording control program of positioning device
US7974639B2 (en) * 2005-02-04 2011-07-05 Qualcomm Incorporated Method and apparatus for performing position determination with a short circuit call flow
US7176833B2 (en) * 2005-04-26 2007-02-13 Sony Ericsson Mobile Communications Ab Portable electronic devices, methods and computer program products using activity-triggered GPS updates
JP2009500967A (en) * 2005-07-07 2009-01-08 クゥアルコム・インコーポレイテッド Method and apparatus for providing location information
US7714779B2 (en) * 2005-10-28 2010-05-11 Broadcom Corporation Method and apparatus for providing a global secure user plane location (SUPL) service

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20040198386A1 (en) * 2002-01-16 2004-10-07 Dupray Dennis J. Applications for a wireless location gateway
US20040152470A1 (en) * 2003-02-04 2004-08-05 Spain David Stevenson Location estimation of wireless terminals though pattern matching of signal-strength differentials
US20050148346A1 (en) * 2003-12-30 2005-07-07 Maloney John E. TDOA/GPS hybrid wireless location system

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
BIACS Z ET AL: "The Qualcomm/SnapTrack Wireless-Assisted GPS Hybrid Positioning System and Results from Initial Commercial Deployments", PROCEEDINGS OF THE INSTITUTE OF NAVIGATION (ION) GPS, 24 September 2002 (2002-09-24), pages 378 - 384, XP002325138 *

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109959894A (en) * 2017-12-26 2019-07-02 深圳市优必选科技有限公司 Localization method and terminal device
CN109959894B (en) * 2017-12-26 2021-06-04 深圳市优必选科技有限公司 Positioning method and terminal equipment

Also Published As

Publication number Publication date
US8965393B2 (en) 2015-02-24
JP2007316067A (en) 2007-12-06
US20060240841A1 (en) 2006-10-26
US20090280829A1 (en) 2009-11-12
EP2027483A1 (en) 2009-02-25

Similar Documents

Publication Publication Date Title
US8965393B2 (en) Estimating the location of a wireless terminal based on assisted GPS and pattern matching
US7848762B2 (en) Computationally-efficient estimation of the location of a wireless terminal based on pattern matching
US7753278B2 (en) Estimating the location of a wireless terminal based on non-uniform locations
US7899467B2 (en) Estimating the location of a wireless terminal based on the traits of the multipath components of a signal
US7257414B2 (en) Estimating the Location of a Wireless Terminal Based on Non-Uniform Probabilities of Movement
US7734298B2 (en) Estimating the location of a wireless terminal based on signal path impairment
US20080299993A1 (en) Computationally-Efficient Estimation of the Location of a Wireless Terminal Based on Pattern Matching
US8571577B2 (en) Estimating the location of a wireless terminal based on signal path impairment
US10547735B2 (en) Calibration of measurement bias of a barometric sensor in a wireless terminal
US8493205B2 (en) Search area reduction based on indoor detection for estimating the location of a wireless terminal
US20210325565A1 (en) Estimation of Reference Barometric Pressure by Using Dissimilar Pressure References
US11927680B2 (en) Estimation of barometric pressure measurement bias based on global navigation satellite system signals

Legal Events

Date Code Title Description
DPE2 Request for preliminary examination filed before expiration of 19th month from priority date (pct application filed from 20040101)
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 07756889

Country of ref document: EP

Kind code of ref document: A1

WWE Wipo information: entry into national phase

Ref document number: 2007756889

Country of ref document: EP

NENP Non-entry into the national phase

Ref country code: DE