基于粒子滤波和地图匹配的融合室内定位  

Fused Indoor Localization Based on Particle Filtering and Map Matching

作　　者：周瑞[1] 鲁翔 卢帅 李志强[1] 桑楠[1] ZHOU Rui;LU Xiang;LU Shuai;LI Zhi-qiang;and SANG Nan(School of Information and Software Engineering, University of Electronic Science and Technology of China Chengdu 610054)

机构地区：[1]电子科技大学信息与软件工程学院,成都610054

出　　处：《电子科技大学学报》2018年第3期415-420,共6页Journal of University of Electronic Science and Technology of China

基　　金：国家科技支撑计划(2012BAH44F00)

摘　　要：为提高室内定位的精确性与合理性,该文提出使用粒子滤波融合Wi Fi指纹定位和行人航位推算,应用室内地图对定位结果进行匹配与矫正。地图匹配中,首先通过室内地图约束粒子的不恰当转移来解决粒子的穿墙问题,然后采用基于回退的穿墙矫正算法对行走轨迹中的穿墙现象进行矫正。仿真实验中,经过粒子滤波融合后估计的行走轨迹更加接近真实轨迹,优于Wi Fi指纹算法和行人航位推算算法估计的轨迹,而经过地图匹配与矫正后,定位精度和合理性得到进一步提高。In order to improve the accuracy of localization, the paper applies particle filtering to fuse Wi Fi fingerprinting and pedestrian dead reckoning（PDR）. The map matching algorithm. The map matching algorithm first makes use of the indoor map to constrain the improper transitions of particles to reduce wall-crossing problems of them and then corrects wall-crossing problems of trajectories with a trace-back method. Evaluations show that the trajectories of the fused solution are closer to the real trajectories than Wi Fi fingerprinting and PDR, and after map matching the trajectories are more accurate and reasonable.

关 键 词：室内定位 地图匹配 粒子滤波 行人航位推算 WiFi指纹 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]