摘要
针对Kalman滤波(UKF)不能解决非线性算法的难点,在Kalman滤波的算法上加以改进。由于(UKF)算法需要利用无迹变换(UT)求解非奇异协方差矩阵的平方根,但在求解奇异协方差矩阵或滤波计算时会有较大的误差,导致算法的精度无法保证。提出了一种基于修正测量UT变换的修正测量UKF算法来处理奇异协方差矩阵来解决这一问题,,并通过仿真验证了该方法的有效性。
Directed at the difficulty that Kalman Filtering cannot solve the pain points of non-linear algorithms,an Unscented Kalman Filter(UKF)is proposed.This algorithm needs to use the unscented transformation(UT)to find the square root of a non-singular covariance matrix,but it is solving Or a large error will occur in the filtering calculation,and the accuracy of the algorithm cannot be guaranteed.In order to analyze this problem,a UT transform based on modified measurement is proposed to deal with the singular covariance matrix,which constitutes the modified measurement UKF algorithm,and the effectiveness of this method is proved by simulation.
作者
崔灿
刘攀
张敏
CUI Can;LIU Pan;ZHANG Min(School of Mechanical Engineering,Hubei Univ.of Tech.,Wuhan 430068,China;2 Engineering and Technology College.Hubei Univ.of Tech.,Wuhan 430068,China)
出处
《湖北工业大学学报》
2021年第4期4-7,共4页
Journal of Hubei University of Technology
关键词
无迹滤波
UT变换
修正量测
奇异矩阵
unsmoothed filtering
ut transformation
corrected measurement
singular matrix
