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
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.
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