摘要
针对室内环境中的非视距(NLOS)导致单一超宽带(UWB)定位出现较大误差的问题,提出基于无迹卡尔曼滤波(UKF)的超宽带/惯性导航系统(INS)紧组合定位方法。优化UWB量测方程,利用导航方程误差状态量简化卡尔曼滤波的预测和校正环节,通过萨格-胡萨(Sage-Husa)自适应估计并利用滤波器新息值对过程和测量噪声进行在线辨识,使得模型白噪声更接近真实情况,利用野值处理方法降低非视距对定位精度的影响。仿真实验结果表明,与传统扩展卡尔曼滤波(EKF)和UKF滤波方案相比较,本文提出基于UKF的组合定位模型能有效抑制非视距误差的影响并提高定位精度。
An ultra-wide band/inertial navigation system(INS) tight integrated positioning method based on unscented Kalman filter(UKF) was proposed to solve the problem of significant error of single ultra-wide band(UWB) localization caused by non-line-of-sight(NLOS) in the indoor environment.The UWB measurement equation was optimized,the error state of the navigation equation was used to simplify the prediction and correction of the Kalman filtering,and the process and measurement noise were identified online through the Sage-Husa adaptive estimation and the filter’s innovation value,so that the white noise of the model was closer to a real condition,and the outlier processing method was used to reduce the influence of non-line-ofsight on the positional accuracy.The results of the emulation experiment indicate that contrast with the conventional extended Kalman filter(EKF) and UKF filtering schemes,the integrated positioning model based on UKF can effectively suppress the influence of non-line-of-sight error and improve the positional accuracy.
作者
孙伟
安晟均
SUN Wei;AN Shengjun(School of Geomatics,Liaoning Technical University,Fuxin,Liaoning 123000,China)
出处
《导航定位学报》
CSCD
2022年第6期68-74,共7页
Journal of Navigation and Positioning
基金
2019辽宁省“兴辽英才计划”青年拔尖人才项目(XLYC1907064)
辽宁工程技术大学学科创新团队资助项目(LNTU20TD-06)
2018年度辽宁省“百千万人才工程”人选科技活动资助项目(辽百千万立项[2019]45号)。
关键词
超宽带
无迹卡尔曼滤波
自适应滤波
室内定位
非视距
ultra-wide band
unscented Kalman filter
adaptive filtering
indoor localization
non-line-of-sight
