Method for position estimation using generalized error distributions
First Claim
1. A method for use in a wireless location system, comprising:
- obtaining field data, wherein said field data have baseline or location dependent values to be used in a signal correlation model;
analyzing said field data to obtain (1) said signal correlation model and associated measurement parameters, (2) correlation matrix rules, and (3) a model for a priori position;
computing weights 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, and computing an inverse covariance matrix;
performing an iterative search over a geographical region to find a location with a maximum a posteriori (MAP) metric;
determining that a stopping condition has been reached; and
reporting the geographic position with the largest MAP metric;
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, and wherein said iterative search includes a MAP metric computation that uses the covariance matrix, an error model and a measurement parameter table.
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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.
16 Citations
20 Claims
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1. A method for use in a wireless location system, comprising:
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obtaining field data, wherein said field data have baseline or location dependent values to be used in a signal correlation model; analyzing said field data to obtain (1) said signal correlation model and associated measurement parameters, (2) correlation matrix rules, and (3) a model for a priori position; computing weights 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, and computing an inverse covariance matrix; performing an iterative search over a geographical region to find a location with a maximum a posteriori (MAP) metric; determining that a stopping condition has been reached; and reporting the geographic position with the largest MAP metric; 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, and wherein said iterative search includes a MAP metric computation that uses the covariance matrix, an error model and a measurement parameter table. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20)
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Specification