自适应渐消EKF方法及其在卫星跟踪中的应用

针对在系统不能确切建模或模型误差随时间改变等场合下，传统扩展卡尔曼滤波方法及其改进算法估计误差较大甚至引起滤波发散等问题，将基于新息序列对状态噪声协方差矩阵实时估计的方法引入到渐消EKF中，提出了一种自适应渐消扩展卡尔曼滤波方法，推导了相关公式并详细给出了新方法的计算流程。采用单星对卫星仅测角被动定轨跟踪的例子对算法性能进行了对比分析。仿真结果表明，与传统EKF方法及其改进算法相比，该方法在估计精度、滤波收敛速度以及对初始状态误差的适应性等方面，显著提高了非线性滤波器的性能。

An adaptive fading extended Kalman filtering method and its application for satellite-to-satellite tracking

While the system model can not be accurately established or the model error changes with time,the traditional extended Kalman filter(EKF) and its modification forms have large estimated errors and even bring filter divergence,so that a new adaptive fading extended Kalman filtering(AFEKF) method is put forward based on the real-time estimation of the covariance matrix of system noise using the innovation sequences.The relevant equations are deduced in details and the working procedure is also presented.Its p...