Enhancements to linear least squares localization through reference selection and ML estimation

Date
2008-03-04
Advisor
Instructor
Source Title
IEEE Wireless Communications and Networking Conference, WCNC 2008
Print ISSN
Electronic ISSN
Publisher
IEEE
Volume
Issue
Pages
284 - 289
Language
English
Type
Conference Paper
Journal Title
Journal ISSN
Volume Title
Abstract

Linear least squares (LLS) estimation is a low complexity but sub-optimum method for estimating the location of a mobile terminal (MT) from some distance measurements. It requires selecting one of the fixed terminals (FTs) as a reference FT for obtaining a linear set of expressions. However, selection of the reference FT is commonly performed arbitrarily in the literature. In this paper, a method for selection of the reference FT is proposed, which improves the location accuracy compared to a fixed selection of the reference FT. Moreover, a covariancematrix based LLS estimator is proposed in line of sight (LOS) and non-LOS (NLOS) environments which further improves accuracy since the correlations between the observations are exploited. Simulation results prove the effectiveness of the proposed techniques. © 2008 IEEE.

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Book Title
Keywords
Least-squares (LS) estimation, Linearization, Maximum likelihood estimation (MLE), Reference selection, Wireless localization, Channel capacity, Curve fitting, Electric appliances, Estimation, Geodesy, Least squares approximations, Port terminals, Surface reconstruction, Wireless telecommunication systems
Citation
Published Version (Please cite this version)