
Research Article
Robust RSS-Based Localization in Mixed LOS/NLOS Environments
@INPROCEEDINGS{10.1007/978-3-030-41114-5_49, author={Yinghao Sun and Gang Wang and Youming Li}, title={Robust RSS-Based Localization in Mixed LOS/NLOS Environments}, proceedings={Communications and Networking. 14th EAI International Conference, ChinaCom 2019, Shanghai, China, November 29 -- December 1, 2019, Proceedings, Part I}, proceedings_a={CHINACOM}, year={2020}, month={2}, keywords={Source localization Received signal strength (RSS) Line-of-sight/non-line-of-sight (LOS/NLOS) Robust weighted least squares (RWLS) Semidefinite relaxation (SDR)}, doi={10.1007/978-3-030-41114-5_49} }
- Yinghao Sun
Gang Wang
Youming Li
Year: 2020
Robust RSS-Based Localization in Mixed LOS/NLOS Environments
CHINACOM
Springer
DOI: 10.1007/978-3-030-41114-5_49
Abstract
In this paper, we propose a robust received signal strength (RSS) based localization method in mixed line-of-sight/non-line-of-sight (LOS/NLOS) environments, where additional path losses caused by NLOS signal propagations are included. Considering that the additional path losses vary in a dramatic range, we express the additional path losses as the sum of a balancing parameter and some error terms. By doing so, we formulate a robust weighted least squares (RWLS) problem with the source location and the balancing parameter as unknown variables, which is, simultaneously, robust to the error terms. By employing the S-Lemma, the RWLS problem is transformed into a non-convex optimization problem, which is then approximately solved by applying the semidefinite relaxation (SDR) technique. The proposed method releases the requirement of knowing specific information about the additional path losses in the previous study. Simulation results show that the proposed method works well in both dense and sparse NLOS environments.