UWB positioning enhancement using Markov chain in indoor NLOS environment

作     者：Li Shaoxian Lii Fan Wang Chengrui Hou Yanzhao Li Shaoxian;Lü Fan;Wang Chengrui;Hou Yanzhao

作者机构：International SchoolBeijing University of Posts and TelecommunicationsBeijing 100876China School of Information and Communication EngineeringBeijing University of Posts and TelecommunicationsBeijing 100876China 

出 版 物：《The Journal of China Universities of Posts and Telecommunications》 (中国邮电高校学报（英文版）)

年 卷 期：2020年第27卷第4期

页      面：54-58,98页

核心收录：

学科分类：0810[工学-信息与通信工程] 1205[管理学-图书情报与档案管理] 08[工学] 0839[工学-网络空间安全] 0804[工学-仪器科学与技术] 080402[工学-测试计量技术及仪器] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：supported by the National Natural Science Foundation of China ( 61701042)。 

主　　题：wireless location time of arrival(TOA) ultra-wide band(UWB) Markov chain fingerprint matching 

摘      要：The accuracy of the positioning system in indoor environment is often affected by none-line-of-sight(NLOS) propagation. In order to improve the positioning accuracy in indoor NLOS environment, a method used ultra-wide-band(UWB) technology, which based on time of arrival(TOA) principle, combining Markov chain and fingerprint matching was proposed. First, the TOA algorithm is used to locate the target tag. Then the Markov chain is used to identify if blocking happened and revise the position result. And the fingerprint matching is used to further improve the position accuracy. Finally, an experiment system was built to test the accuracy of the proposed method and the traditional Kalman filter method. The experimental results show that, compared with the traditional Kalman filter method, the proposed method can improve the positioning accuracy in indoor NLOS environment.