An UWB/PDR Fusion Algorithm Based on Improved Square Root Unscented Kalman Filter

被引：0
|
作者：
Liu, Yuan [1 ]
Li, Sheng [1 ]
Sun, Qiang [1 ]
Chang, Chenfei [2 ]
He, Guangjian [3 ]
Kang, Xiao [4 ]
机构：
[1] Nanjing Univ Sci & Technol, Sch Automat, Nanjing 210094, Peoples R China
[2] Northern Res Inst NJUST, Tianjin 300220, Peoples R China
[3] Guangzhou Metro Grp Co Ltd, Guangzhou 510220, Peoples R China
[4] China North Vehicle Res Inst, Res & Dev Ctr, Beijing 100072, Peoples R China
来源：
PROCEEDINGS OF THE 38TH CHINESE CONTROL CONFERENCE (CCC) | 2019年
关键词：
indoor positioning; UWB technology; Pedestrian Dead Reckoning; improved square root unscented Kalman filter algorithm;
D O I：
10.23919/chicc.2019.8866374
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
How to improve the accuracy of indoor positioning is a hot issue in the research of wireless indoor positioning technology. In order to solve the problem that Ultra Wideband (UWB) technology cannot locate accurately under the condition of non-line of sight (NLOS), this paper proposes an indoor positioning method combining UWB and Pedestrian Dead Reckoning (PDR).The method utilizes the advantages of high frequency noise characteristics of PDR to suppress the NLOS error generated by UWB. Furthermore, in order to get better integration of UWB and PDR, an improved square root unscented Kalman filter (ISR-UKF) is proposed. The simulation results show that the improved algorithm proposed in this paper can effectively improve the indoor positioning accuracy, and ensure the stability and continuity of the positioning system.
引用
收藏
页码：4124 / 4129
页数：6
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