Abstract:

The fluctuation of received signal strength (RSS) and access points (AP) outage are the major limit to wireless local area network (WLAN) based positioning accuracy. This paper proposes a data fusion algorithm based on particle filter and Kalman filter in order to realize a low-cost, high-precision WLAN/ magnetic, angular rate, and gravity (MARG) integrated positioning system using MARG sensors in the Smartphone. The system fuses the complementary information from WLAN and MARG positioning techniques to correct the positioning error due to the fluctuation of RSS and the accumulative error of the sensors due to senor noises. The experimental results in indoor WLAN environments indicate that the positioning accuracy of the proposed system is reduced by 62% and 91%, respectively, as compared with WLAN-based system and MARG-based system. Meanwhile, the scope of positioning is also effectively expanded.