NLOS环境下基于UWB的定位算法研究  

Research on Location Algorithm Based on UWB in NLOS Environment

作　　者：徐淑萍[1] 郭宇 王双 张玉西 XU Shu-ping;GUO Yu;WANG Shuang;ZHANG Yu-xi(School of computer science,Xi'an University of technology,Shaanxi,Xi'an 710000,China)

机构地区：[1]西安工业大学计算机学院,陕西西安710000

出　　处：《计算机仿真》2023年第4期439-443,共5页Computer Simulation

基　　金：国家地方联合工程实验室基金项目(GSYSJ2018012);陕西省教育厅专项科学研究计划(17JK0381)。

摘　　要：为解决室内非视距(NLOS)环境下定位及机器人定位过程中由于非视距环境下,噪声存在异常值误差过大的问题,提出了两种基于Chan-Taylor协同算法来抑制NLOS误差的方案。一种为结合了卡尔曼滤波的抑制方案,另一种为依据测量特征统计的距离重构方案,从多种定位算法组合出发,有效避免了高噪声和NLOS误差的影响,并通过动静态定位测试分析两种方案的定位精度。结果表明,两种方案均能降低NLOS环境下的定位误差,但NLOS误差抑制算法的效果较优,适应性更强。In order to solve the problem of excessive outlier error due to noise in the indoor non-line-of-sight(NLOS)environment and robot positioning process due to the non-line-of-sight environment,two solutions based on the Chan-Taylor collaborative algorithm to suppress the NLOS error are proposed.The first is a suppression scheme combined with Kalman filtering.The other is a distance reconstruction scheme based on measurement feature statistics.Starting from the combination of multiple positioning algorithms,the effects of high noise and NLOS errors are effectively avoided,and the positioning accuracy of the two solutions is analyzed through dynamic and static positioning tests.The results show that both schemes can reduce positioning errors in the NLOS environment,but the NLOS error suppression algorithm is more effective and more adaptable.

关 键 词：室内定位 非视距 卡尔曼滤波 

分 类 号：TN911.7[电子电信—通信与信息系统]