基于多传感器融合的室内定位算法研究

An Indoor Pedestrian Localization Algorithm Based on Multi-sensor Information Fusion

对于现有的室内定位算法存在低精度、低实用性和低传感器利用率等问题,提出了一种基于多传感器融合的粒子滤波室内定位技术,将智能移动终端与室内定位相结合,利用粒子滤波器过滤定位结果。采用行人航位推算(PDR)技术和RSSI定位技术获取行人位置信息,提高了定位精度与可靠性。此外,通过定位结果实时上传至服务器,同步递增构建位置指纹库,以适应室内环境的动态变化。实验结果表明,基于多传感器融合的定位技术与基于Wi-Fi的定位技术相比提高了定位精度与可靠性。

Considering that existing indoor localization algorithms have the problems such as low accuracy, high cost indeployment and maintenance,lack of robustness and low sensor utilization,this paper proposes a particle filter algorithm based on multi-sensor fusion. The algorithm combines the smart mobile terminal with indoor localization,and filters the result of localization with the particle filter. In this paper,a dynamic interval particle filter algorithm based on pedestrian dead reckoning （ PDR） information and RSSI localization information is used to improve the filtering precision and the stability. Moreover, the localization results will be uploaded to the server in real time,and the location fingerprint database will be built incrementally to adapt to the dynamic changes of the indoor environment. Experimental results show that the algorithm based on multi-sensor fusion improves the localization accuracy and robustness compared with the location algorithm based on Wi-Fi.