@inproceedings{d0387ac92a4f411981e060a5ce1df66e,
title = "Non-line-of-sight positioning algorithm based on robust principal component analysis",
abstract = "Non-Line-of-Sight (NLOS) propagation problems badly degrade the accuracy of wireless mobile positioning algorithms, which incurs a large positive bias in the Time-of-Arrival (TOA) measurements. Under several assumptions, the Hankel matrix of TOA data can be decomposed into a low-rank distance matrix and a sparse error matrix. This paper utilizes the robust principal component analysis (RPCA) method to solve the decomposition problem. After estimating the distance, the positioning problem can use existing Line-of-Sight (LOS) based algorithms to calculate the coordinate of the mobile station (MS). Simulation results show that our method outperforms other existing NLOS positioning methods and the RPCA based matrix decomposition process can eliminate NLOS effect efficiently.",
keywords = "Low-rank, Non-line-of-sight, RPCA, Sparse, TOA",
author = "Xiong, \{Zhu Lin\} and Celun Liu and Wei Du and Xie, \{Ze Bin\}",
year = "2014",
doi = "10.4028/www.scientific.net/AMR.998-999.889",
language = "English",
isbn = "9783038351849",
series = "Advanced Materials Research",
publisher = "Trans Tech Publications Ltd.",
pages = "889--893",
booktitle = "Advances in Applied Sciences, Engineering and Technology II",
address = "Switzerland",
note = "2014 International Conference on Applied Sciences, Engineering and Technology, ICASET 2014 ; Conference date: 28-07-2014 Through 29-07-2014",
}