一种基于UWB/INS自适应抗差卡尔曼滤波算法  

An Adaptive Robust Kalman Filter Algorithm Based on UWB / INS

作　　者：侯华[1] 代超娜 李峻辉 郭宏洋 HOU Hua;DAI Chao-na;LI Jun-hui;GUO Hong-yang(School of Information and Electrical Engineering,Hebei University of Engineering,Handan Hebei 056000,China)

机构地区：[1]河北工程大学信息与电气工程学院,河北邯郸056000

出　　处：《计算机仿真》2023年第12期496-501,共6页Computer Simulation

摘　　要：针对矿井环境下UWB定位精度受多径干扰和非视距误差影响的问题,提出了一种基于UWB/INS自适应抗差卡尔曼滤波算法。算法通过调节状态协方差矩阵的预测残差来建立统计参量,结合调节观测噪声协方差矩阵的抗差因子,自适应调整预测值和观测值所占的权重。实验结果表明,与UWB定位算法相比,所提算法最大定位误差减小了2.14m,最小定位误差减小了0.08m,平均定位误差减小了1.1m;与UWB/INS自适应卡尔曼滤波算法相比,所提算法最大定位误差减小了0.98m,最小定位误差减小了0.02m,平均定位误差减小了0.5m。Aiming at the problem that UWB positioning accuracy is affected by multipath interference and nonline-of-sight error in the mine environment,an adaptive robust Kalman filter algorithm based on UWB/INS is pro⁃posed.The statistical parameters are established by adjusting the prediction residual of the state covariance matrix.Combined with adjusting the robust factor of the observation noise covariance matrix,the weight of the prediction val⁃ue and the observation value is adjusted adaptively.The experimental results show that compared with the UWB posi⁃tioning algorithm,the maximum positioning error of the proposed algorithm is reduced by 2.14m,the minimum posi⁃tioning error is reduced by 0.08m,and the average positioning error is reduced by 1.1m.Compared with the UWB/INS adaptive Kalman filter algorithm,the maximum positioning error of the proposed algorithm is reduced by 0.98m,the minimum positioning error is reduced by 0.02m,and the average positioning error is reduced by 0.5m,which has high positioning accuracy.

关 键 词：自适应滤波 抗差因子 预测残差 

分 类 号：TP391.9[自动化与计算机技术—计算机应用技术]