CA2746279A1 - Method for position estimation using generalized error distributions - Google Patents

Method for position estimation using generalized error distributions Download PDF

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Publication number
CA2746279A1
CA2746279A1 CA2746279A CA2746279A CA2746279A1 CA 2746279 A1 CA2746279 A1 CA 2746279A1 CA 2746279 A CA2746279 A CA 2746279A CA 2746279 A CA2746279 A CA 2746279A CA 2746279 A1 CA2746279 A1 CA 2746279A1
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Canada
Prior art keywords
recited
tdoa
correlation
map
weighted
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Granted
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CA2746279A
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French (fr)
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CA2746279C (en
Inventor
Pete A. Boyer
Rashidus S. Mia
Edward Joseph Segall
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Skyhook Holding Inc
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Trueposition Inc
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Publication date
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Publication of CA2746279A1 publication Critical patent/CA2746279A1/en
Application granted granted Critical
Publication of CA2746279C publication Critical patent/CA2746279C/en
Expired - Fee Related legal-status Critical Current
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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
    • G01S5/0278—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
    • G01S5/06—Position of source determined by co-ordinating a plurality of position lines defined by path-difference measurements
    • 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
    • G01S5/10—Position of receiver fixed by co-ordinating a plurality of position lines defined by path-difference measurements, e.g. omega or decca systems

Abstract

A method for improving the results of radio location systems that incorporate weighted least squares optimization generalizes the weighted least squares method by using maximum a posteriori (MAP) probability metrics to incorporate characteristics of the specific positioning problem (e.g., UTDOA). Weighted least squares methods are typically used by TDOA and related location systems including TDOA/
AOA and TDOA/GPS hybrid systems. The incorporated characteristics include empirical information about TDOA errors and the probability distribution of the mobile position relative to other network elements. A
technique is provided for modeling the TDOA error distribution and the a priori mobile position. A method for computing a MAP decision metric is provided using the new probability distribution models. Testing with field data shows that this method yields significant improvement over existing weighted least squares methods.

Claims (7)

1. An error detection method, comprising:
obtaining field data (402), wherein said field data have baseline or location dependent values to be used in said signal correlation model;
analyzing said field data (403) to obtain (1) a signal correlation model and associated measurement parameters (405), (2) correlation matrix rules (404), and (3) a model for a priori position (406);
computing weights (407) for the measurements based on an estimated variability of the measurement;
using the weights along with the correlation matrix rules to generate a covariance matrix (409), and computing an inverse covariance matrix (410);
performing an iterative search over a geographical region to find a location with a maximum a posteriori (MAP) metric (415);
determining that a stopping condition has been reached (419); and reporting the geographic position with the largest MAP metric as the location solution.
2. A method as recited in claim 1, further comprising generating a table providing a mapping between the measurement parameters for a skew and a correlation value for the measurement.
3. A method as recited in claim 1, further comprising generating a table providing a mapping between the measurement parameters for a skew and the number of baselines.
4. A method as recited in claim 1, wherein further comprising analyzing the correlation between different receiver ports linking the location receiver to an external antenna, providing correlation values and rules for their application.
5. A method as recited in claim 1, wherein said iterative search includes a resolution loop in which a geographic search space resolution is reduced in each iteration and new test points are generated via interpolation.
6. A method as recited in claim 5, wherein the search is re-centered at the previous iteration's minimum error point before proceeding, wherein test points within the current geographical region search space are individually searched and a MAP metric is computed for each test point.
7. A method as recited in claim 1, wherein the iterative search includes a MAP
metric computation that uses the covariance matrix, error model and measurement parameter table.
CA2746279A 2008-12-30 2009-12-14 Method for position estimation using generalized error distributions Expired - Fee Related CA2746279C (en)

Applications Claiming Priority (3)

Application Number Priority Date Filing Date Title
US12/346,146 US7956808B2 (en) 2008-12-30 2008-12-30 Method for position estimation using generalized error distributions
US12/346,146 2008-12-30
PCT/US2009/067886 WO2010077819A1 (en) 2008-12-30 2009-12-14 Method for position estimation using generalized error distributions

Publications (2)

Publication Number Publication Date
CA2746279A1 true CA2746279A1 (en) 2010-07-08
CA2746279C CA2746279C (en) 2012-05-01

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CA2746279A Expired - Fee Related CA2746279C (en) 2008-12-30 2009-12-14 Method for position estimation using generalized error distributions

Country Status (11)

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US (2) US7956808B2 (en)
EP (1) EP2384549A4 (en)
JP (1) JP2012514210A (en)
KR (1) KR20110112829A (en)
CN (1) CN102273081B (en)
AU (1) AU2009333351B2 (en)
BR (1) BRPI0923869A2 (en)
CA (1) CA2746279C (en)
IL (1) IL213099A (en)
MX (1) MX2011006511A (en)
WO (1) WO2010077819A1 (en)

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BRPI0923869A2 (en) 2018-05-29
CN102273081B (en) 2014-07-30
IL213099A (en) 2016-07-31
WO2010077819A1 (en) 2010-07-08
AU2009333351B2 (en) 2013-05-02
US20100164781A1 (en) 2010-07-01
MX2011006511A (en) 2011-09-01
EP2384549A1 (en) 2011-11-09
CN102273081A (en) 2011-12-07
KR20110112829A (en) 2011-10-13
EP2384549A4 (en) 2016-01-06
JP2012514210A (en) 2012-06-21
IL213099A0 (en) 2011-07-31
US20110205108A1 (en) 2011-08-25
CA2746279C (en) 2012-05-01
AU2009333351A1 (en) 2010-07-08
US7956808B2 (en) 2011-06-07
WO2010077819A8 (en) 2011-07-07
US8138976B2 (en) 2012-03-20

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