Fundamental limits and improved algorithms for linear least-squares wireless position estimation
Author
Guvenc, I.
Gezici, Sinan
Sahinoglu Z.
Date
2010-09-22Source Title
Wireless Communications and Mobile Computing
Print ISSN
1530-8669
Publisher
John Wiley & Sons
Volume
12
Issue
12
Pages
1037 - 1052
Language
English
Type
ArticleItem Usage Stats
154
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128
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Abstract
In this paper, theoretical lower bounds on performance of linear least-squares (LLS) position estimators are obtained, and performance differences between LLS and nonlinear least-squares (NLS) position estimators are quantified. In addition, two techniques are proposed in order to improve the performance of the LLS approach. First, a reference selection algorithm is proposed to optimally select the measurement that is used for linearizing the other measurements in an LLS estimator. Then, a maximum likelihood approach is proposed, which takes correlations between different measurements into account in order to reduce average position estimation errors. Simulations are performed to evaluate the theoretical limits and to compare performance of various LLS estimators.
Keywords
Cramer-rao lower bound (CRLB)least-squares (LS) estimation
Maximum likelihood (ML)
Time-of-arrival (TOA)
Wireless positioning
Cramer-rao lower bound
Least Square
Linear least squares
Lower bounds
Maximum likelihood approaches
Nonlinear least squares
Position estimation
Selection algorithm
Theoretical limits
Time-of-arrival
Wireless positioning
Algorithms
Cramer-Rao bounds
Maximum likelihood
Estimation
Permalink
http://hdl.handle.net/11693/21360Published Version (Please cite this version)
http://dx.doi.org/10.1002/wcm.1029Collections
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