[01] Jiacheng Ni, School of Information Engineering, Yancheng Teachers University, Yancheng, China. [02] Wenmin Xia, School of Information Engineering, Yancheng Teachers University, Yancheng, China. [03] Litong Sun, School of Information Engineering, Yancheng Teachers University, Yancheng, China. [04] Chaogang Xu, School of Information Engineering, Yancheng Teachers University, Yancheng, China. [05] Yuqi Yang, School of Information Engineering, Yancheng Teachers University, Yancheng, China. [06] Hao Yang, School of Information Engineering, Yancheng Teachers University, Yancheng, China; Jiangsu Provincial Key Constructive Laboratory for Big Data of Psychology and Cognitive Science, Yancheng Teachers University, Yancheng, China.

The WiFi fingerprint location method is greatly affected by spatial ambiguity and temporal instability. Due to the practicability of WiFi facilities and the widespread layout in various indoor scenes, indoor positioning based on WiFi fingerprint has become the most attractive technical means. This paper combines WiFi signal and geomagnetic signals to achieve effective collaborative positioning method and track tracking. In details, the main work of this paper is to design an effective location and trajectory tracking method by cooperating with WiFi and geomagnetism. Firstly, we propose a robust localization algorithm for RSS signal level; secondly, we propose a real-time trajectory matching algorithm for geomagnetic signals; finally, we design a particle filter to realize the user's trajectory collaborative tracking. The ultimate goal is to achieve a high-precision and robust positioning algorithm based on WiFi signal and geomagnetic signal, so that it can not only achieve high-precision single point static positioning using WiFi, but also realize real-time trajectory tracking combined with IMU reading. This method can not only realize high-precision single point static positioning with WiFi, but also realize real-time trajectory tracking combined with IMU reading. Therefor, our approach provides a new idea to cooperatively employ WiFi and geomagnetic signals for future indoor positioning research.

Cooperative Localization, WiFi, Geomagnetic Signals

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