TDOA Based Indoor Positioning with NLOS Identification by Machine Learning

被引：0
|
作者：
Wu, Chi [1 ]
Hou, Hongwei [1 ]
Wang, Wenjin [1 ]
Huang, Qing [1 ]
Gao, Xiqi [1 ]
机构：
[1] Southeast Univ, Natl Mobile Commun Res Lab, Nanjing 210096, Jiangsu, Peoples R China
来源：
2018 10TH INTERNATIONAL CONFERENCE ON WIRELESS COMMUNICATIONS AND SIGNAL PROCESSING (WCSP) | 2018年
基金：
中国国家自然科学基金;
关键词：
Positioning; machine learning; NLOS identification; TDOA; LOCALIZATION; ESTIMATOR;
D O I：
暂无
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
Indoor positioning technology has broad application prospects, such as intelligent indoor navigation and security monitoring. However, due to the complex and varied indoor scattering environment, non-line-of-sight (NLOS) propagation seriously affects the accuracy of positioning. In this paper, we investigate the NLOS propagation identification for time difference of arrival (TDOA) based positioning in indoor environment. We analyze the correlations between measured distances based on TDOA and select measured distances to identify NLOS data. A new NLOS classification method is proposed based on machine learning to improve positioning accuracy. Numerical results demonstrate the performance of the proposed positioning method.
引用
收藏
页数：6
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