一种精确协方差估计的转换量测卡尔曼滤波方法

传统转换量测卡尔曼滤波(CMKF)方法对误差协方差矩阵进行估计时,采用了线性近似的方式。当量测方位误差较大时,无法准确估计出协方差矩阵。针对该问题,提出了一种基于精确协方差估计的CMKF方法,可有效抑制方位误差对协方差估计的影响。仿真结果表明该方法可有效抑制量测方位误差的影响,提升目标跟踪的定位精度。

A Conversion Measurement Kalman Filtering Method of Accurate Covariance Estimation

The linear approximation mode is adopted in the estimation of error covariance matrix by using traditional conversion measurement Kalman filtering（CMKF）method.When the bearing error is large,covariance matrix could not be estimated exactly.To solve this problem,this paper presents a CMKF method based on accurate covariance estimation,which can effectively suppress the influence of bearing error on covariance estimation.The simulation results show that this method can effectively restrain the influence of bearing errors and improve the locating precision of target tracking.