摘要
针对超宽带(UWB)定位技术受到环境中非视距(NLOS)因素的影响,造成定位精度低、定位稳定性差的问题,提出对UWB采集的原始数据进行两次粒子滤波,从而实现精准的动态目标定位。第一次粒子滤波算法用于存储每个锚点测量距离与误差关系模型。第二次粒子滤波在更新阶段根据距离误差模型调节权重,进一步约束估计的目标粒子,实现更精准的动态目标定位。不同环境下的实验结果表明:该算法能有效抑制NLOS误差的影响,在非视距严重的环境中定位精度能达到0.29 m,相比于系统提供的三边测量定位算法精度提高48.21%,相比传统粒子滤波精度提高17.14%,明显提高了NLOS传播环境下的动态目标定位精度。
Aiming at the problem that ultra wide band( UWB) positioning technology is highly impacted by nonline of sight( NLOS) factors from an environment,which results in low positioning precision and poor positioning stability,an approach is proposed for accurate dynamic target positioning by applying particle filtering twice on the raw data collected by the UWB. The first particle filtering is used to save the relational model between the measured distance and the error model of each anchor. Based on the model,the second particle filter is used by assigning particles with different weights to improve the positioning accuracy. Experimental results in different environments show that the proposed algorithm can effectively suppress the influence of NLOS error. With this algorithm implemented,the positioning accuracy of the dynamic object reaches 0. 29 m at the moment when NLOS errors appear to be serious,which is an improvement of 48. 21 % and 17. 14 % when compared with the triangulation algorithm provided by the UWB system and traditional particle filtering-based approach. The dynamic object positioning accuracy is remarkably improved in NLOS environment.
作者
何永平
刘冉
付文鹏
梁高丽
付余路
张华
HE Yongping;LIU Ran;FU Wenpeng;LIANG Gaoli;FU Yulu;ZHANG Hua(School of Information Engineering,Southwest University of Science and Technology,Mianyang 621010,China)
出处
《传感器与微系统》
CSCD
2020年第8期46-49,54,共5页
Transducer and Microsystem Technologies
基金
四川省科技计划资助项目(2019YFH0161)
国家自然科学基金资助项目(61601381,61471306,61701421)
国家核能开发科研资助项目([2016]1295)。
关键词
超宽带(UWB)
室内定位
非视距误差
粒子滤波
ultra wide band(UWB)
indoor positioning
non-line of sight(NLOS)error
particle filtering
