Tunnel Vehicle RSSI Positioning Algorithm Based on LMLF Model

被引：0
|
作者：
Wang, Yaofei [1 ]
Yin, Xunhe [2 ]
Cai, Guoqiang [3 ]
Wang, Ge [1 ]
Guo, Shan [3 ]
Liang, Kexin [3 ]
机构：
[1] Beijing Jiaotong Univ, Sch Elect & Informat Engn, State Key Lab Rail Traff Control & Safety, Beijing, Peoples R China
[2] Beijing Jiaotong Univ, Sch Elect & Informat Engn, Beijing, Peoples R China
[3] Beijing Jiaotong Univ, Sch Traff & Transportat, State Key Lab Rail Traff Control & Safety, Beijing, Peoples R China
来源：
PROCEEDINGS OF 2019 4TH INTERNATIONAL CONFERENCE ON CLOUD COMPUTING AND INTERNET OF THINGS (CCIOT 2019) | 2019年
关键词：
LMLF model; RSSI positioning; Gauss-median filtering; wireless sensor network; Tunnel positioning;
D O I：
10.1109/cciot48581.2019.8980342
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Tunnel positioning of vehicles usually has large errors and disturbances. In this paper, the tunnel electromagnetic wave propagation model is analyzed. Based on this, an RSSI positioning algorithm based on LMLF(Linear Modified Log Function) model is proposed. The constraint factor in this algorithm can reduce the positioning error of the fitting curve, and Gaussian-median filtering technology enhances the Robustness of ranging. Experiments show that the RSSI positioning algorithm based on LMLF greatly improves the accuracy and anti-interference ability of RSSI positioning.
引用
收藏
页码：29 / 32
页数：4
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