WO2011084063A1 - Procédé de détermination de l'emplacement d'un dispositif mobile, dispositif mobile et système pour un tel procédé - Google Patents

Procédé de détermination de l'emplacement d'un dispositif mobile, dispositif mobile et système pour un tel procédé Download PDF

Info

Publication number
WO2011084063A1
WO2011084063A1 PCT/NL2011/050015 NL2011050015W WO2011084063A1 WO 2011084063 A1 WO2011084063 A1 WO 2011084063A1 NL 2011050015 W NL2011050015 W NL 2011050015W WO 2011084063 A1 WO2011084063 A1 WO 2011084063A1
Authority
WO
WIPO (PCT)
Prior art keywords
determining
mobile device
localization
parameter
reference stations
Prior art date
Application number
PCT/NL2011/050015
Other languages
English (en)
Inventor
Paul Havinga
Bram Dil
Original Assignee
Ambient Holding B.V.
Universiteit Twente
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 Ambient Holding B.V., Universiteit Twente filed Critical Ambient Holding B.V.
Publication of WO2011084063A1 publication Critical patent/WO2011084063A1/fr

Links

Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO 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
    • G01S5/00—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations
    • G01S5/02—Position-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
    • G01S5/0205—Details
    • G01S5/021—Calibration, monitoring or correction
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO 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
    • G01S5/00—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations
    • G01S5/02—Position-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
    • G01S5/0278—Position-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 involving statistical or probabilistic considerations
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO 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
    • G01S5/00—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations
    • G01S5/02—Position-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
    • G01S5/14—Determining absolute distances from a plurality of spaced points of known location

Definitions

  • the present invention relates a method for determining the location of a mobile device.
  • the present invention further relates to a mobile device adapted for use in such a method.
  • the present invention also relates to a system comprising such a mobile device.
  • TDOA Time Difference Of Arrival
  • TOF Time Of Flight
  • UWB Ultra Wide Band
  • AOA Angle of Arrival
  • RSS-based localization is still an active and popular field of research.
  • the localization approaches described in this patent are also applicable in conjunction with other localization techniques like TDOA, TOF and UWB .
  • Fingerprinting requires a predeployment phase in which the signal strength is recorded to stationary infrastructure nodes at several locations.
  • the recorded measurements, taken at a particular position, represent the fingerprint of that particular position. So the localization area is divided into a large set of positions and associated fingerprints. Localization is done by finding the closest match in the database of fingerprints. This means that the RSS
  • RSS- and range-based localization algorithms assume that the signal strength decay over distance follows a distribution that is known beforehand. This distribution is used for converting one or several signal strength measurements into distance estimates. Empirical studies show that the environment has a significant influence on the RSS and therefore on aforementioned distribution ( [RAP96] ) .
  • Range- free localization approaches use radio connectivity ( [DVH01] , [AMO03] , [MOB04] and [ENH04] ) or proximity information ( [PIT03] and [ROC04] ) .
  • Radio connectivity [DVH01] , [AMO03] , [MOB04] and [ENH04]
  • proximity information [PIT03] and [ROC04]
  • Existing localization algorithms based on radio connectivity assume that the transmission range ( [MOB04] ) or the deployment distribution is uniform and known beforehand ( [DVH01] ,
  • radio connectivity information is just a quantization of signal strength measurements. It is logical that this quantization decreases the localization accuracy compared to using unquantized signal strength measurements.
  • These conditions can be environment related like humidity, temperature and moving objects. Moreover, these conditions also include the orientation and directionality of the antenna. It is known that these conditions have a large influence on the RSS and are therefore inherent to RSS-based localization. This means that most existing localization algorithms are not well suited in dynamic environments.
  • Aforementioned problems can partly be solved by deploying a dense localization infrastructure and periodically
  • the present invention provides a method for determining the location of a mobile device, comprising the steps of: receiving from at least two reference stations a wirelessly transmitted signal, the location of the reference stations being known, wherein the signal is influenced by at least one parameter; determining at least one property of the received signal; determining an educated guess for at least one of the influencing parameters; estimating the at least one influencing parameters based on the at least one determined property and the at least one guessed,
  • the educated guess serves as an initial value for an estimator being used to estimate the
  • the educated guess may be provided by some further algorithm, it may be some predetermined value that has been determined to be a suitable value for a representative set of the possible circumstances, or it may even be some random initial value, although the later might result in either more computational effort to reach a sufficiently accurate estimation, or a less accurate estimation .
  • This method comprises two estimating steps.
  • the person skilled in the art will naturally understand that these steps do not necessarily need to be two distinct steps, but, in a preferred embodiment of the present invention, are combined in a single estimating step that estimates the distances to the at least two reference stations, only producing the estimated, influencing
  • parameter as a by-product, which may be used in a further method as the educated guess in a subsequent estimation to determine an updated position based upon a next determined value of the at least one property.
  • the optimizer is also provided with a set of constraints, the constraints
  • the signal strength diminishes with the distance to the transmitter, or in other words, the path loss exponent is positive.
  • the optimiser With the condition that the path loss exponent is strictly positive, the accuracy of the estimation can be improved.
  • the determined properties of the received signal comprise at least one of: the Received Signal Strength, RSS; the Time Difference of Arrival, TDoA; the Time of Flight, ToF; and the Angle of Arrival, AoA.
  • the distance to the reference stations can be derived from the Received
  • Signal Strength based on the knowledge that the transmitted signal attenuates quadraticly with the distance travelled.
  • two or three reference stations are required to determine the location of the mobile device.
  • the possible locations of the mobile station can be reduced to a hyperbolic line based on the Time Difference of the Arrival of the transmitted messages. If another pair of reference stations is used (which requires a total of at least three reference stations) , the intersection of the two hyperbolic lines specifies the location of the mobile device .
  • Time of Flight it is again possible to derive the distance from the reference stations.
  • time lags For example a time lag due to decoding of the received signal and processing of the received message.
  • some form of syncing the clock of the mobile device to the reference stations is needed.
  • the Angle of Arrival of the signal is used to determine the location.
  • the mobile device determines the angle between at least three reference stations to determine its location, or the Angle of Arrival of two reference stations in combination with the orientation of the mobile device.
  • the reference stations measure the Angle of Arrival of the signal from the mobile device. In this case, only two reference stations are needed to determine the location.
  • the at least one influencing parameter comprises at least one of: the path loss exponent; the transmission power; the antenna
  • the present invention provides a mobile device comprising: a receiver for receiving a wirelessly transmitted signal from at least two reference stations with known location, wherein the signal is
  • received signal evaluation means connected to the receiver, for determining at least one property of the received signal
  • guessing means for determining an educated guess for at least one of the influencing parameters
  • a parameter estimator connected to the received signal evaluation means and the guessing means, for determining an estimate of the influencing parameter based on the determined property and the guessed
  • a distance estimator connected to the received signal evaluation means and the parameter estimator, for estimating the distances to the at least two reference stations based on the at least one determined property and the at least one estimated, influencing parameter; and location determination means for determining the location of the device based on the distances to the at least two reference stations, the location determination means being connected to the distance estimator.
  • the above embodiment comprises two estimators, the parameter estimator and the distance estimator.
  • these estimators do not necessarily need to be two distinct estimators, but, in a preferred embodiment of the present invention, are combined in a single estimator that estimates the distances to the at least two reference stations, only producing the estimated, influencing parameter as a byproduct .
  • a mobile device wherein the received signal evaluation means determine at least one of: the Received Signal Strength, RSS; the Time Difference of Arrival, TDoA; the Time of Flight, ToF; and the Angle of Arrival, AoA.
  • the present invention provides a mobile device, wherein the at least one parameter comprises at least one of: the path loss exponent; the transmission power; the antenna orientation; the antenna gain; the temperature; and the humidity.
  • the present invention also provides a system for determining the location of a mobile device, comprising: at least two reference stations comprising a transmitter; and a mobile device according to the present invention.
  • FIG. 1 is a reprentation of a wireless
  • FIG. 2 is a flowchart of the new localization method .
  • FIG. 3 is a flowchart of the new localization method .
  • FIG. 4 is a flowchart of the existing localization method .
  • FIG. 5 is a flowchart autocalibrating the path loss exponent on the basis of one or several signal strength measurements using the new localization method.
  • FIG. 6 is a flowchart autocalibrating the transmission power and/or antenna orientation and gain on the basis of one or several signal strength measurements using the new localization method.
  • FIG. 7 is a flowchart autocalibrating additive external factors on the basis of one or several TOF
  • FIG. 8 is a flowchart autocalibrating
  • multiplicative external factors on the basis of one or several TOF measurements using the new localization method.
  • FIG. 9 is a flowchart autocalibrating additive and multiplicative external factors on the basis of one or several TOF measurements using the new localization method.
  • System 300 in FIG 1 represents a wireless localization network.
  • System 300 includes infrastructure nodes 301, 302, 303, 304, 305, 306 and a node 307 that locates itself on the basis of several distance measurements 308, 309, 310, 311, 312, 313 to infrastructure nodes.
  • localization network 300 the blind node and/or the
  • FIG 4 shows a flow diagram of method 200 of the localization method described in the prior art section. This method distinguishes two phases, namely the calibration phase 205 and the localization phase 206.
  • the calibration phase 205 is a phase that calibrates the required nuisance parameters 202.
  • Aforementioned phase consists of performing calibration measurements 203 and on the basis of these measurements this approach calibrates the nuisance parameters 204 and outputs nuisance parameter values 225.
  • Aforementioned calibrated values of the nuisance parameters are used as input for the localization phase 206.
  • the blind node and/or the infrastructure nodes first perform localization measurements 102 as described in system 300.
  • the distances are estimated 104 on the basis of these measurements 102 and calibrated nuisance parameters 225.
  • the localization algorithm 105 estimates the position on the basis of the distance
  • the localization algorithm 105 could also evaluate other input 106, like inertial measurements.
  • the striped lines indicate that this is optional.
  • FIG 2 shows a flow diagram of the method 100 of the new localization method.
  • the blind node and/or the infrastructure nodes first perform localization measurements 102 as described in system 300.
  • the new localization method calibrates a specified set of nuisance parameters 103.
  • the distances 104 are estimated on the basis of the measurements 102 and calibrated nuisance parameters 103.
  • the localization algorithm 105 estimates the position on the basis of the distance estimates 104.
  • the localization algorithm 105 could also evaluate other input 106.
  • the position estimate of the localization algorithm provides input 107 for the (re- ) calibration of the nuisance
  • Method 110 represents the autocalibration of the nuisance parameters. Although, the representation of method 110 may seem to indicate that the autocalibration of nuisance parameters is an iterative process. Method 110 only indicates that the autocalibration of the nuisance
  • parameters is based on the localization measurements.
  • the proposed method can use any estimator for estimating the position by processing aforementioned information. So method 100 is independent of the used estimator.
  • the current implementation uses the Gauss -Newton Method as the estimator.
  • FIG 3 represents processes 103, 104, 105 and 107 as one block and therefore supports aforementioned
  • Embodiments of the invention are but are not limited to:
  • FIG. 5 represents a localization algorithm that autocalibrates the path loss exponent 132 on the basis of at least one or several signal strength measurements 131.
  • the values of one or more nuisance parameters are based on educational guesses 108.
  • FIG. 6 represents a localization algorithm that autocalibrates the transmission power and/or orientation and gain of antenna 142 on the basis of at least one or several signal strength measurements 141.
  • the values of one ore more nuisance parameters are based on educational guesses 108.
  • FIG. 7 represents a localization algorithm that autocalibrates the additive external factors 152 on the basis of at least one or several TOF measurements 151.
  • the values of zero or more nuisance parameters are based on educational guesses 108.
  • FIG. 8 represents a localization algorithm that autocalibrates the multiplicative external factors 162 on the basis of at least one or several TOF measurements 161.
  • the values of zero or more nuisance parameters are based on educational guesses 108.
  • FIG. 9 represents a localization algorithm that autocalibrates the additive and multiplicative external factors 172 on the basis of at least one or several TOF measurements 171.
  • the values of zero or more nuisance parameters are based on educational guesses 108.
  • the maximum likelihood expression could be maximized by any estimator like the Gauss-Newton Method. The rest of the parameters are estimated with educated guesses.
  • Hashemi H. The indoor radio propagation channel, Proc. IEEE, July 1993, pp. 943- 996.
  • RAP96 Rappaport T.S., Wireless Communication: Principles and Practice, Prentice Hall, ISBN 013 3755633, 1996.
  • RADAR An in- building RF-based user location and tracking system. INFOCOM 2000, pages 775-784, March 2000.

Abstract

L'invention concerne un procédé permettant de déterminer l'emplacement d'un dispositif mobile, comprenant les étapes consistant à : recevoir, à partir d'au moins deux stations de référence, un signal transmis sans fil, l'emplacement des stations de référence étant connu, le signal étant influencé par au moins un paramètre ; déterminer au moins une propriété du signal reçu ; déterminer une estimation bien renseignée pour au moins l'un des paramètres d'influence ; estimer le ou les paramètres d'influence sur la base de la ou des propriétés déterminées et du ou des paramètres d'influence estimés ; estimer les distances jusqu'aux deux stations de référence ou plus sur la base de la ou des propriétés déterminées et du ou des paramètres d'influence estimés ; et déterminer la position du dispositif mobile sur la base des distances jusqu'aux deux stations de référence ou plus.
PCT/NL2011/050015 2010-01-07 2011-01-07 Procédé de détermination de l'emplacement d'un dispositif mobile, dispositif mobile et système pour un tel procédé WO2011084063A1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
NL2004070A NL2004070C2 (en) 2010-01-07 2010-01-07 Method for determining the location of a mobile device, mobile device and system for such method.
NL2004070 2010-01-07

Publications (1)

Publication Number Publication Date
WO2011084063A1 true WO2011084063A1 (fr) 2011-07-14

Family

ID=42727577

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/NL2011/050015 WO2011084063A1 (fr) 2010-01-07 2011-01-07 Procédé de détermination de l'emplacement d'un dispositif mobile, dispositif mobile et système pour un tel procédé

Country Status (2)

Country Link
NL (1) NL2004070C2 (fr)
WO (1) WO2011084063A1 (fr)

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2015125001A (ja) * 2013-12-25 2015-07-06 三菱電機株式会社 測位装置及び測位方法
WO2015191086A1 (fr) * 2014-06-13 2015-12-17 Hewlett-Packard Development Company, L.P. Détermination de position d'un dispositif informatique mobile
EP2984502A4 (fr) * 2013-04-12 2016-10-12 Hewlett Packard Entpr Dev Lp Détermination de la distance d'un dispositif mobile

Citations (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6246861B1 (en) * 1997-11-06 2001-06-12 Telecommunications Research Lab. Cellular telephone location system
US20050176442A1 (en) 2004-02-11 2005-08-11 Wen-Hua Ju Estimating the location of inexpensive wireless terminals by using signal strength measurements
EP1575328A1 (fr) 2004-02-23 2005-09-14 France Telecom Procédé et dispositif de localisation d'un terminal dans un réseau local sans fil
EP1617601A2 (fr) 2004-04-20 2006-01-18 Universiteit Twente Algorithme distribué de localisation de précision pour les réseaux sans fil ad-hoc
EP1689126A1 (fr) 2005-02-08 2006-08-09 Alcatel Service de localisation dans un réseau local sans fil
US20070111735A1 (en) 2005-11-15 2007-05-17 Bhaskar Srinivasan Hybrid localization in wireless networks
WO2007056738A2 (fr) 2005-11-07 2007-05-18 Qualcomm Incorporated Localisation dans des reseaux locaux sans fil et dans d'autres reseaux sans fil
US20070117572A1 (en) 2005-11-18 2007-05-24 Tomtom International B.V. Efficient Location and Tracking of Mobile Subscribers
US20080080429A1 (en) * 2006-10-03 2008-04-03 Cisco Technology, Inc. Minimum variance location estimation in wireless networks
US20090154371A1 (en) 2006-05-08 2009-06-18 Skyhook Wireless, Inc. Estimation of position using wlan access point radio propagation characteristics in a wlan positioning system

Patent Citations (12)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6246861B1 (en) * 1997-11-06 2001-06-12 Telecommunications Research Lab. Cellular telephone location system
US20050176442A1 (en) 2004-02-11 2005-08-11 Wen-Hua Ju Estimating the location of inexpensive wireless terminals by using signal strength measurements
EP1575325A2 (fr) 2004-02-11 2005-09-14 Avaya Technology Corp. Estimation de la position de terminaux sans fil à faible coût en utilisant des mesures d'intensité de signal
EP1575328A1 (fr) 2004-02-23 2005-09-14 France Telecom Procédé et dispositif de localisation d'un terminal dans un réseau local sans fil
EP1617601A2 (fr) 2004-04-20 2006-01-18 Universiteit Twente Algorithme distribué de localisation de précision pour les réseaux sans fil ad-hoc
EP1689126A1 (fr) 2005-02-08 2006-08-09 Alcatel Service de localisation dans un réseau local sans fil
US20060176849A1 (en) 2005-02-08 2006-08-10 Alcatel Geographical localisation service
WO2007056738A2 (fr) 2005-11-07 2007-05-18 Qualcomm Incorporated Localisation dans des reseaux locaux sans fil et dans d'autres reseaux sans fil
US20070111735A1 (en) 2005-11-15 2007-05-17 Bhaskar Srinivasan Hybrid localization in wireless networks
US20070117572A1 (en) 2005-11-18 2007-05-24 Tomtom International B.V. Efficient Location and Tracking of Mobile Subscribers
US20090154371A1 (en) 2006-05-08 2009-06-18 Skyhook Wireless, Inc. Estimation of position using wlan access point radio propagation characteristics in a wlan positioning system
US20080080429A1 (en) * 2006-10-03 2008-04-03 Cisco Technology, Inc. Minimum variance location estimation in wireless networks

Non-Patent Citations (24)

* Cited by examiner, † Cited by third party
Title
C. LIU; K. WU; T. HE: "Sensor localization with ring overlapping based on comparison of received signal strength indicator", IEEE MOBILE AD-HOC AND SENSOR SYSTEMS, October 2004 (2004-10-01)
D.NICULESCU; B.NATH: "Ad hoc positioning systems", IEEE GLOBECOM, 2001
F.GUSTAFSSON; F.GUNNARSSON: "Localization based on observations linear in log range", IFAC WORLD CONGRESS, 2008
GUSTAFSSON F ET AL: "Localization based on observations linear in log range", IFAC PROCEEDINGS VOLUMES (IFAC-PAPERSONLINE) - PROCEEDINGS OF THE 17TH WORLD CONGRESS, vol. 17, no. 1, 2008, pages 1 - 6, XP002601753, DOI: 10.3182/20080706-5-KR-1001.2802 *
HASHEMI H.: "The indoor radio propagation channel", PROC. IEEE, July 1993 (1993-07-01), pages 943 - 996
J.A.COSTA; N.PATWARI; A.O.HERO: "Distributed Weighted Multidimensional Scaling for Node Localization in Sensor Networks", ACM TRANSACTIONS ON SENSOR NETWORKS, vol. 2, no. 1, February 2006 (2006-02-01), pages 39 - 64, XP058232213, DOI: doi:10.1145/1138127.1138129
K. YEDAVALLI; B. KRISHNAMACHARI; S. RAVULA; B. SRINIVASAN: "Ecolocation: A sequence based technique for RF- only localization in wireless sensor networks", IEEE IPSN, April 2005 (2005-04-01)
K.WHITEHOUSE; C.KARLOF; D.CULLER: "A Practical Evaluation of Radio Signal Strength for Ranging-based Localization", MOBILE COMPUTING AND COMMUNICATIONS REVIEW, vol. 11, no. 1, 2007
K.WHITEHOUSE; D.CULLER: "Mobile Networks and Applications Journal", June 2003, ACM PRESS, article "Macro-Calibration in Sensor/Actuator Networks"
L.HU; D.EVANS: "Localization for Mobile Sensor Networks", TENTH ANNUAL INTERNATIONAL CONFERENCE ON MOBILE COMPUTING AND NETWORKING, 2004
MAZUELAS S ET AL: "Robust Indoor Positioning Provided by Real-Time RSSI Values in Unmodified WLAN Networks", IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING, vol. 3, no. 5, 1 October 2009 (2009-10-01), IEEE, US, pages 821 - 831, XP011278679, ISSN: 1932-4553, DOI: 10.1109/JSTSP.2009.2029191 *
N. PATWARI: "Location estimation in sensor networks", PHD THESIS, 2005
N. PATWARI; A.O. HERO; M.PERKINS; N.S.CORREAL; R.J.O'DEA: "Relative Location Estimation in Wireless Sensor Networks", IEEE TRANSACTIONS ON SIGNAL PROCESSING, SPECIAL ISSUE ON SIGNAL PROCESSING IN NETWORKS, vol. 51, no. 8, August 2003 (2003-08-01), pages 2137 - 2148, XP055179698, DOI: doi:10.1109/TSP.2003.814469
N.PATWARI; R.J.O'DEA; Y.WANG: "IEEE Vehicular Technology Conference", May 2001, SPRING, article "Relative Location in Wireless Networks"
P. BAHL; V. N. PADMANABHAN: "RADAR: An in- building RF-based user location and tracking system", INFOCOM, March 2000 (2000-03-01), pages 775 - 784, XP001042792
PATWARI, N.; HERO, A.O.: "Signal Strength Localization Bounds in Ad Hoc and Sensor Networks when Transmit Powers are Random", SENSOR ARRAY AND MULTICHANNEL PROCESSING, 12 July 2006 (2006-07-12), pages 299 - 303, XP010935284, DOI: doi:10.1109/SAM.2006.1677207
R.A.MALANEY: "Nuisance Parameters and Location Accuracy in Log-Normal Fading Models", IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, vol. 6, March 2007 (2007-03-01), pages 937 - 947, XP011175195, DOI: doi:10.1109/TWC.2007.05247
R.NAGPAL; H.SHROBE; J.BACHRACH: "Organizing a Global Coordinate System from Local Information on an Ad Hoc Sensor Network", 2ND INTERNATIONAL WORKSHOP ON INFORMATION PROCESSING IN SENSOR NETWORKS, April 2003 (2003-04-01)
RAPPAPORT T.S.: "Wireless Communication: Principles and Practice", 1996, PRENTICE HALL
ROBERT A MALANEY: "Nuisance Parameters and Location Accuracy in Log-Normal Fading Models", IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, vol. 6, no. 3, 1 March 2007 (2007-03-01), IEEE SERVICE CENTER, PISCATAWAY, NJ, US, pages 937 - 947, XP011175195, ISSN: 1536-1276, DOI: 10.1109/TWC.2007.05247 *
RONG PENG; MIHAIL L. SICHITIU: "Probabilistic Localization for Outdoor Wireless Sensor Networks", ACM SIGMOBILE MOBILE COMPUTING AND COMMUNICATIONS, vol. 11, January 2007 (2007-01-01), pages 53 - 64
S.DULMAN; P.HAVINGA: "Statistically enhanced localization schemes for randomly deployed wireless sensor networks", DEST INTERNATIONAL WORKSHOP ON SIGNAL PROCESSING FOR SENSOR NETWORKS, 2004
T.HE; C.HUANG; B.M.BLUM; J.STANKOVIC; T.ABDELZAHER: "Range-free localization schemes for large scale sensor networks", MOBICOM, September 2003 (2003-09-01), pages 81 - 95, XP001186710, DOI: doi:10.1145/938985.938995
V. RAMADURAI; M. L. SICHITIU: "Localization in wireless sensor networks: A probabilistic approach", PROC. OF THE 2003 INTERNATIONAL CONFERENCE ON WIRELESS NETWORKS, June 2003 (2003-06-01), pages 275 - 281

Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP2984502A4 (fr) * 2013-04-12 2016-10-12 Hewlett Packard Entpr Dev Lp Détermination de la distance d'un dispositif mobile
US9706358B2 (en) 2013-04-12 2017-07-11 Hewlett Packard Enterprise Development Lp Distance determination of a mobile device
JP2015125001A (ja) * 2013-12-25 2015-07-06 三菱電機株式会社 測位装置及び測位方法
WO2015191086A1 (fr) * 2014-06-13 2015-12-17 Hewlett-Packard Development Company, L.P. Détermination de position d'un dispositif informatique mobile
US10866303B2 (en) 2014-06-13 2020-12-15 Hewlett Packard Enterprise Development Lp Determining the location of a mobile computing device

Also Published As

Publication number Publication date
NL2004070C2 (en) 2011-07-11

Similar Documents

Publication Publication Date Title
Xiao et al. An RSSI based DV-hop algorithm for wireless sensor networks
Liu et al. Survey of wireless based indoor localization technologies
US10809350B2 (en) Hybrid fingerprinting/OTDOA positioning techniques and systems
KR102299605B1 (ko) 다중 경로 완화를 이용한 위치 결정 시스템 및 방법
KR100938806B1 (ko) 알에프수신신호세기의 확률적 필터링을 이용한무선센서노드 위치추적방법
KR20170063389A (ko) 강건하고 정확한 ｒｓｓｉ 기반 위치 추정을 위한 시스템 및 방법
Dil et al. On the calibration and performance of RSS-based localization methods
Zhou et al. Construction of local anchor map for indoor position measurement system
Hongyang et al. A robust location algorithm with biased extended Kalman filtering of TDOA data for wireless sensor networks
Qiu et al. BLE-based collaborative indoor localization with adaptive multi-lateration and mobile encountering
Moghtadaiee et al. Design protocol and performance analysis of indoor fingerprinting positioning systems
NL2004070C2 (en) Method for determining the location of a mobile device, mobile device and system for such method.
Kuxdorf-Alkirata et al. Reliable and low-cost indoor localization based on bluetooth low energy
Tarrio et al. An RSS localization method based on parametric channel models
Kouyoumdjieva et al. Experimental evaluation of precision of a proximity-based indoor positioning system
Xu et al. Variance-based fingerprint distance adjustment algorithm for indoor localization
WO2007129939A1 (fr) amélioration de la précision des informations d'emplacement et/ou de chemin d'un client mobile dans un réseau sans fil
Jabbar et al. A novel power tuning anchors localization algorithm for mobile wireless sensor nodes
Jung et al. Peer to peer signal strength characteristic between IoT devices for distance estimation
Liu et al. Research and improvement of DVHOP localization algorithm in wireless sensor networks
Abed et al. An adaptive K-NN based on multiple services set identifiers for indoor positioning system with an ensemble approach
EP3523673A1 (fr) Procédé et système de localisation d'un noeud aveugle
Huang et al. Location tracking in mobile ad hoc networks using particle filters
Pires et al. An efficient calibration method for RSSI-based location algorithms
García et al. Wireless sensor network localization using hexagonal intersection

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 11702290

Country of ref document: EP

Kind code of ref document: A1

NENP Non-entry into the national phase

Ref country code: DE

122 Ep: pct application non-entry in european phase

Ref document number: 11702290

Country of ref document: EP

Kind code of ref document: A1