Improved robust toa-based localization via nlos balancing parameter estimation

Document Type

Article

Publication Date

6-1-2019

Abstract

In this paper, the time-of-arrival-based localization problem under mixed line-of-sight/non-line-of-sight (LOS/NLOS) conditions is addressed. Previous studies show that existing robust methods perform well in dense NLOS environments, but generally perform badly in sparse NLOS environments. To alleviate this problem, we introduce a 'balancing parameter' related to the NLOS errors and formulate a new robust weighted least squares (RWLS) problem with the source position and the NLOS balancing parameter as the estimation variables. The proposed method does not require the statistics of NLOS errors and the path status. By leveraging the S-Lemma, the RWLS problem is transformed into a non-convex optimization problem, which is then relaxed into a convex semidefinite program. Simulation results show that the proposed method works well for both the sparse and dense NLOS environments.

Identifier

85067984232 (Scopus)

Publication Title

IEEE Transactions on Vehicular Technology

External Full Text Location

https://doi.org/10.1109/TVT.2019.2911187

e-ISSN

19399359

ISSN

00189545

First Page

6177

Last Page

6181

Issue

6

Volume

68

Grant

61571249

Fund Ref

National Natural Science Foundation of China

This document is currently not available here.

Share

COinS