城市环境下基于降维Kalman滤波的室内导航算法  

RESPECTIVE KALMAN FILTER ALGORITHM FOR INDOOR LOCALIZATION UNDER URBAN ENVIRONMENT

作　　者：许龙[1] 

机构地区：[1]华中科技大学建筑与城市规划学院,武汉市珞喻路1037号430074

出　　处：《测绘信息与工程》2010年第4期40-42,共3页Journal of Geomatics

摘　　要：提出了一种适用于室内超宽带定位的降维Kalman滤波算法,结合LSE算法与降维Kalman滤波算法进行定位求解,以数值仿真试验及物理试验验证了其有效性。We approved a dimension reducing kalman filter（DRKF）which fit for the UWB indoor localization system.In the situation of UWB indoor localization,the LSE optimize algorithm,DRKF and TOA spherical surface localization algorithm were combined together to form an indoor localization algorithm.The validity of the new algorithm was validated via numerical simulation and physical experimentation.

关 键 词：城市环境 室内定位 KALMAN滤波 TOA算法 不相关性 

分 类 号：P228[天文地球—大地测量学与测量工程]