Fundamental limits and improved algorithms for linear least-squares wireless position estimation

Authors:
Ismail Guvenc;Sinan Gezici;Zafer Sahinoglu
Affiliations:
DOCOMO Communications Laboratories USA, Inc., 3240 Hillview Avenue, Palo Alto, CA 94304, USA;Department of Electrical and Electronics Engineering, Bilkent University, Bilkent, Ankara 06800, Turkey;Mitsubishi Electric Research Labs, 201 Broadway, Cambridge, MA 02139, USA
Venue:
Wireless Communications & Mobile Computing
Year:
2012

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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. Copyright © 2010 John Wiley & Sons, Ltd. (Part of this work was presented at the IEEE Wireless Communications and Networking Conference (WCNC) 2008 and at the IEEE International Conference on Communications (ICC) 2008.)