基于数据融合的WLAN/MARG组合定位系统

接收信号强度（received signal strength, RSS）浮动和无线接入点缺失是制约无线局域网（wireless local area network, WLAN）定位精度的主要问题。利用智能终端已有的MARG（magnetic，angular rate，and gravity）传感器，设计了基于粒子滤波和卡尔曼滤波的数据融合算法，实现了一个低成本高精度的WLAN/MARG组合定位系统。该系统利用WLAN和MARG定位技术的互补特性，有效校正了由RSS浮动引起的定位误差和由传感器噪声引起的累积误差。室内WLAN环境下的实验结果表明，本文所提系统，相比WLAN和MARG定位系统，定位均方根误差分布减少了62%和91%，并且有效扩大了系统应用范围。

WLAN/MARG integrated positioning system using data fusion

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.