基于平方根求积卡尔曼滤波器的弹道目标跟踪

Tracking ballistic target based on square root quadrature Kalman filter

针对再入阶段的弹道目标跟踪问题,提出运用平方根求积卡尔曼滤波器(SRQKF)估计目标的状态.所提出的算法是求积卡尔曼滤波(QKF)算法的平方根实现.该算法传播了目标状态的均值和协方差的平方根,确保了协方差矩阵的对称性和半正定性,改进了数值精度和稳定性,但其计算复杂性稍有增加.仿真实验表明,所提出算法的估计精度优于QKF算法和扩展卡尔曼滤波(EKF)算法,是一种很有效的非线性滤波方法.

In order to track the ballistic re-entry target,a square root quadrature Kalman filter（SRQKF） is presented to estimate the target state.The proposed algorithm is the square root implementation of the quadrature Kalman filter（QKF）. The square root quadrature Kalman filter propagates the mean and the square root of the covariance,which guarantees the symmetry and positive semi-definiteness of the covariance matrix,improves numerical stability and numerical accuracy,but at the expense of increased computational complexity.The simulation experiments show that,the estimation accuracy of the new algorithm outperforms that of the QKF and the extended Kalman fitering algorithms,and the method is an effective nonlinear filtering method.