Enhancements to linear least squares localization through reference selection and ML estimation
Date
Advisor
Instructor
Source Title
Print ISSN
Electronic ISSN
Publisher
Volume
Issue
Pages
Language
Type
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.