An Improved Constrained Least Squares Localization Algorithm in NLOS Propagating Environment

Yejia Yin; Jingyu Hua; Fangni Chen; Weidang Lu; Dongming Wang; Jiamin Li

Machine Learning and Intelligent Communications. Third International Conference, MLICOM 2018, Hangzhou, China, July 6-8, 2018, Proceedings

Research Article

An Improved Constrained Least Squares Localization Algorithm in NLOS Propagating Environment

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@INPROCEEDINGS{10.1007/978-3-030-00557-3_9,
    author={Yejia Yin and Jingyu Hua and Fangni Chen and Weidang Lu and Dongming Wang and Jiamin Li},
    title={An Improved Constrained Least Squares Localization Algorithm in NLOS Propagating Environment},
    proceedings={Machine Learning and Intelligent Communications. Third International Conference, MLICOM 2018, Hangzhou, China, July 6-8, 2018, Proceedings},
    proceedings_a={MLICOM},
    year={2018},
    month={10},
    keywords={Wireless localization Non-line-of-sight error Constrained least squares Time of arrival},
    doi={10.1007/978-3-030-00557-3_9}
}

Yejia Yin
Jingyu Hua
Fangni Chen
Weidang Lu
Dongming Wang
Jiamin Li
Year: 2018
An Improved Constrained Least Squares Localization Algorithm in NLOS Propagating Environment
MLICOM
Springer
DOI: 10.1007/978-3-030-00557-3_9

Yejia Yin¹, Jingyu Hua¹^,*, Fangni Chen¹, Weidang Lu¹, Dongming Wang², Jiamin Li²

1: Zhejiang University of Technology
2: Southeast University

*Contact email: eehjy@163.com

Abstract

The non-line-of-sight (NLOS) error is a major error source in wireless localization. Therefore, an improved constrained least-squares (CLS) algorithm is put forward to tackle this issue, where the positioning problem is formulated as a mathematical programming problem. And then, the cost function of the optimization is studied and a new one is proposed. Finally, through the presented optimization, we try to minimize the positioning influence of NLOS errors. Moreover, the studied method does not depend on a particular distribution of the NLOS error. Simulation results show that the positioning accuracy is significantly improved over traditional CLS algorithms, even under highly NLOS conditions.

Keywords: Wireless localization Non-line-of-sight error Constrained least squares Time of arrival

Published: 2018-10-12
Appears in: SpringerLink

: http://dx.doi.org/10.1007/978-3-030-00557-3_9