A Novel Kalman Filter Based NLOS Localization Method for Wireless Sensor Networks

被引：3
作者：
Cheng, Long [1 ,2 ]
Shao, Yuchao [1 ]
Wang, Yan [1 ]
机构：
[1] Northeastern Univ, Dept Comp & Commun Engn, Qinhuangdao 066004, Peoples R China
[2] Northeastern Univ, Sch Informat Sci & Engn, Shenyang 110819, Liaoning, Peoples R China
来源：
CLOUD COMPUTING AND SECURITY, PT I | 2017年 / 10602卷
基金：
中国国家自然科学基金;
关键词：
Wireless sensor networks; Localization; Non-line-of-sight; Kalman filter; COOPERATIVE LOCALIZATION; ENVIRONMENTS;
D O I：
10.1007/978-3-319-68505-2_42
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Wireless sensor networks (WSNs) have the focus of research in recent years. Moreover, positioning is very important for wireless sensor networks. However, the positioning accuracy still has large error in the case of non-line-of-sight. In this paper, we propose an improved Kalman filter algorithm to reduce the influence of NLOS error. For the case of NLOS, the measurement residual E-i(k) is updated firstly. This method can effectively reduce the NLOS error, which makes the positioning result more accurate. The simulation results show that the proposed localization algorithm can accurately apply to the normal NLOS location problem.
引用
收藏
页数：12
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