Robust NLOS Bias Mitigation for Hybrid RSS-TOA Based Source Localization Under Unknown Transmission Parameters

被引：17

作者：

Katwe, Mayur ^{[1
]}

Ghare, Pradnya ^{[1
]}

Sharma, Prabhat Kumar ^{[1
]}

机构：

[1] Visvesvaraya Natl Inst Technol, Dept Elect & Commun Engn, Nagpur 440010, Maharashtra, India

来源：

IEEE WIRELESS COMMUNICATIONS LETTERS | 2021年 / 10卷 / 03期

关键词：

Maximum likelihood estimation; Noise measurement; Wireless sensor networks; Upper bound; Programming; Power measurement; Measurement uncertainty; Hybrid localization; unknown transmission parameters; non-line of sight (NLOS) bias mitigation;

D O I：

10.1109/LWC.2020.3037095

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This letter addresses the problem of source localization in non-line of sight (NLOS) environment using received signal strength (RSS) and time of arrival (TOA) measurements when both transmission time and power are unknown. To mitigate the NLOS bias, a robust weighted least square (RWLS) problem is formulated from original non-convex maximum-likelihood (ML) estimation problem using a set of tight approximations. The RWLS problem is further tightened by a novel convex-hull constraint and is ultimately solved using second-order cone programming (SOCP). Simulation results confirm the optimal performance of the proposed robust method in various network scenarios and also validate its excellence over state-of-art methods.

引用

页码：542 / 546

页数：5

共 21 条

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