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

Date
2010-09-22
Advisor
Supervisor
Co-Advisor
Co-Supervisor
Instructor
Source Title
Wireless Communications and Mobile Computing
Print ISSN
1530-8669
Electronic ISSN
Publisher
John Wiley & Sons
Volume
12
Issue
12
Pages
1037 - 1052
Language
English
Type
Article
Journal Title
Journal ISSN
Volume Title
Series
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.

Course
Other identifiers
Book Title
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
Citation
Published Version (Please cite this version)