Comparison of Linearized Kalman Filter and Extended Kalman Filter for Satellite Motion States Estimation

作     者：杨亚非 

作者机构：Control & Simulation CenterHarbin Institute of Technology 

出 版 物：《Journal of Measurement Science and Instrumentation》 (测试科学与仪器（英文版）)

年 卷 期：2011年第2卷第4期

页      面：307-311页

学科分类：0809[工学-电子科学与技术（可授工学、理学学位）] 080902[工学-电路与系统] 08[工学] 

主　　题：扩展卡尔曼滤波器 非线性系统 状态估计 卫星运动 卡尔曼滤波方法 卡尔曼滤波估计 Matlab 测量过程 

摘      要：The performance of the conventional Kalman filter depends on process and measurement noise statistics given by the system model and measurements.The conventional Kalman filter is usually used for a linear system,but it should not be used for estimating the state of a nonlinear system such as a satellite motion because it is difficult to obtain the desired estimation results.The linearized Kalman filtering approach and the extended Kalman filtering approach have been proposed for a general nonlinear system.The equations of satellite motion are described.The satellite motion states are estimated,and the relevant estimation errors are calculated through the estimation algorithms of the both above mentioned approaches implemented in Matlab are estimated.The performances of the extended Kalman filter and the linearized Kalman filter are compared.The simulation results show that the extended Kalman filter is much better than the linearized Kalman filter at the aspect of estimation effect.