径向速度测量推广Kalman滤波的改进

研究了一种把径向速度测量引入推广Kalman滤波 (EKF)的新方法。在对测量方程进行分解和对测量噪声的统计特性进行分析的基础上提出了一种序贯处理结构的推广Kalman滤波算法 ,这种算法相当于对非线性的径向速度函数围绕状态矢量的滤波值而不是预测值线性化 ,因而可以大大减小线性化处理带来的误差。两个不同的MonteCarlo仿真结果说明该算法的估计性能优于传统的推广Kalman滤波。

Improvement on Extended Kalman Filtering With Radial Velocity Measurements

A new algorithm is developed to incorporate the radial velocity measurement into extended Kalman filter. Based on the decomposition of measurement equations and the analysis of measurement noise statistical property, a sequential processing filter algorithm is obtained, which corresponds to the linearization of the nonlinear raidal velocity function around the state filtered value rather than state predicated value and hence can reduce the errors caused by linearization greatly. Two different Monte Carlo simulation results show that the above algorithm is superior to the classic extended Kalman filter algorithm in estimation performance.