无线电工程2024，Vol.54Issue(7)：1721-1731,11.DOI:10.3969/j.issn.1003-3106.2024.07.015
基于UWB和IMU融合的UWB弱信号环境下高精度定位算法
High-precision Positioning Algorithm Based on UWB and IMU Fusion in UWB Weak Signal Environment
摘要
Abstract
To solve the problems that the Global Navigation Satellite System(GNSS)has poor positioning precision in confined space and even cannot locate,and the Ultra-Wide Band(UWB)indoor positioning technology has poor positioning precision and low positioning stability in Non Line of Sight(NLoS)environment.Based on the error state Kalman filter and the fusion of UWB positioning technology and Inertial Measurement Unit(IMU),a UWB positioning algorithm model in UWB weak signal environment is designed to realize centimeter-level positioning in UWB weak signal environment.By optimizing the traditional error state Kalman filter method and fusing the measurement data of UWB and IMU,the problems of poor positioning precision and easy deviation of positioning results of traditional UWB positioning in NLoS environment are solved.The experimental results show that in the navigation laboratory,the precision of the system in the east direction,north axis and OXY plane in the East-North-Sky(ENU)coordinate system is increased by 2.87％,12.02％and 5.71％respectively,and the variance is reduced by 5.80％,18.06％and 5.71％respectively.In the underground channel UWB weak signal environment,the precision of the system in the east direction,north direction and OXY plane is improved by 12.08％,24.10％and 16.08％respectively.The variance is reduced by 8.12％,32.74％and 12.23％,respectively.The proposed algorithm model effectively improves low positioning precision and poor system positioning stability of UWB indoor positioning technology in the case of NLoS,reduces the positioning cost,and has strong practicability.关键词
超宽带/惯性传感器/误差状态卡尔曼滤波/非视距Key words
UWB/IMU/ESKF/NLoS分类
信息技术与安全科学引用本文复制引用
赵阳,王田虎,李文杰,缪千年,沈运哲,黄涛..基于UWB和IMU融合的UWB弱信号环境下高精度定位算法[J].无线电工程,2024,54(7):1721-1731,11.基金项目
江苏省自然科学基金(BK20150247) （BK20150247）
江苏省实践创新项目(XSJCX22_44) （XSJCX22_44）
中车南京浦镇车辆有限公司委托课题(KY30720210001)Jiangsu Provincial Natural Science Foundation of China(BK20150247) （KY30720210001）
Practice Innovation Project of Jiangsu Province(XSJCX22_44) （XSJCX22_44）
The Project Funded by CRRC Nanjing Puzhen Vehicle Co.,Ltd.(KY30720210001) （KY30720210001）
