Improved positioning algorithm based on two step least square in NLOS environments  

作　　者：WU Shi-xun LI Ji-ping-yin LIU Shou 

机构地区：[1]Department of Electronics and Communication Engineering, Central China Normal University, Wuhan 430079, China

出　　处：《The Journal of China Universities of Posts and Telecommunications》2011年第5期58-63,共6页中国邮电高校学报（英文版）

基　　金：supported by the National Natural Science Foundation of China (60572117);the Scientific Research Foundation for the returned Overseas Chinese scholars, State Education Ministry

摘　　要：Non-line-of-sight （NLOS） propagation is a major source of error for accurate time-of-arrival （TOA） location estimation. The two-step least square （LS） method, which does not need any information about the distribution of the NLOS error, has been studied in related researches to provide efficient location estimation of the mobile terminal （MT）. By observing the estimation of the error covariance matrix in the two-step LS method, this paper finds that the measured distances are more suitable than the initial estimated distances by maximum likelihood （ML） algorithm in NLOS environments. Moreover, by making use of the geometry relations among fixed terminals （FTs）, some measured distances which are corrupted by big NLOS errors may be reduced. Further, an iteration method can be adopted to further improve the performance of the algorithm. Accordingly, an improved algorithm based on the two-step LS method is proposed. Simulation results demonstrate that the improved algorithm has better performance than the two-step LS method and converges more quickly. Meanwhile, it is robust in different NLOS environments.Non-line-of-sight （NLOS） propagation is a major source of error for accurate time-of-arrival （TOA） location estimation. The two-step least square （LS） method, which does not need any information about the distribution of the NLOS error, has been studied in related researches to provide efficient location estimation of the mobile terminal （MT）. By observing the estimation of the error covariance matrix in the two-step LS method, this paper finds that the measured distances are more suitable than the initial estimated distances by maximum likelihood （ML） algorithm in NLOS environments. Moreover, by making use of the geometry relations among fixed terminals （FTs）, some measured distances which are corrupted by big NLOS errors may be reduced. Further, an iteration method can be adopted to further improve the performance of the algorithm. Accordingly, an improved algorithm based on the two-step LS method is proposed. Simulation results demonstrate that the improved algorithm has better performance than the two-step LS method and converges more quickly. Meanwhile, it is robust in different NLOS environments.

关 键 词：NLOS propagation TOA least square position algorithm maximum likelihood 

分 类 号：TN915[电子电信—通信与信息系统] P228[电子电信—信息与通信工程]