A novel particle filter approach for indoor positioning by fusing WiFi and inertial sensors

(in lingua inglese)

In this paper, a novel fusion algorithm for indoor positioning is proposed. The filter method is exploited to integrate inertial sensor, WiFi sensor and the map information. Also, local RBPF and global RBPF are introduced into the fusion algorithm. By dividing the indoor environments into several local areas, without computing the global areas, the computation could reduce greatly. Preliminary trial results show that the proposed RBPF algorithm could achieve the positioning accuracy of 1.2 m and it meets the need of indoor positioning. Also, the calculation burden is nearly half of the conventional PF methods.