The Research of Indoor Three-Dimensional Positioning Algorithm Based on Ultra-Wideband Technology

被引:0
作者
Wang, Xin [1 ]
Huang, Zehua [1 ]
Zheng, FuQuan [2 ]
Tian, Xincheng [1 ]
机构
[1] Shandong Univ, Sch Control Sci & Engn, Jinan 250061, Peoples R China
[2] Shandong Acad Sci, Inst Automat, Jinan 250014, Peoples R China
来源
PROCEEDINGS OF THE 39TH CHINESE CONTROL CONFERENCE | 2020年
关键词
Three-dimensional positioning; NLOS; Chan algorithm; Taylor series expansion algorithm;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In the positioning of the target in the three-dimensional indoor scene, the non-line of sight (NLOS) error caused by the occlusion of the obstacle will seriously reduce the positioning accuracy of Chan algorithm. The Taylor series positioning algorithm can suppress the NLOS error, but the algorithm is dependent on the selection of the initial value, and the initial value selection is not suitable, which can lead to the non-convergence of the algorithm. Aiming at the above problems, a fast and accurate Chan-Taylor series joint three-dimensional localization algorithm is proposed. First, the time of arrival (TOA) data obtained by the ultra-wideband (UWB) technology measurement is analyzed by the residual discrimination method, and whether the NLOS error exists in the measured data is identified. Then, aiming at the existence of NLOS error, the positioning result obtained by the Chan algorithm is used as the initial positioning value of the Taylor series positioning algorithm, and the positioning position is further iteratively calculated by the Taylor series expansion method. In the case of the line of sight distance (LOS), a single Chan location algorithm is still used for calculation. The experimental results show that the Chan-Taylor series joint three-dimensional localization algorithm improves the positioning speed and effectively suppresses the adverse effect of NLOS error on the positioning accuracy, and can reach the positioning accuracy of less than 0.2m in 73% case.
引用
收藏
页码:5144 / 5149
页数:6
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