Applied Research of location fingerprint positioning system based on the improved AUKF algorithm

被引：0

作者：

Cao Chunping ^{[1
]}

Chen Ping ^{[1
]}

Wang Yagang ^{[1
]}

机构：

[1] Univ Shanghai Sci & Technol, Sch Opt Elect & Comp Engn, Shanghai 200093, Peoples R China

来源：

2013 32ND CHINESE CONTROL CONFERENCE (CCC) | 2013年

关键词：

location fingerprint positioning; Adaptive Unscented Kalman Filter; real-time tracking;

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：

Because of the signal error existing in mine personnel positioning when using location fingerprint positioning, the paper proposes self-adaptive unscented Kalman filter (Adaptive UKF, AUKF) algorithm. The filtering algorithm can actively suppress signal diverging and compensate for the signal loss brought about by the noise, and further improve the accuracy of the sample signal in location fingerprint positioning method. By associating the accurate signal positioning with the position algorithm, the system can obtain more accurate target location.

引用

页码：4023 / 4027

页数：5