Star-sensor-based predictive Kalman filter for satellite attitude estimation

作     者：林玉荣 邓正隆 

作者机构：1. Department of Control Science and Engineering Harbin Institute of Technology 150001 Harbin China 

出 版 物：《Science in China(Series F)》 (中国科学（F辑英文版）)

年 卷 期：2002年第45卷第3期

页      面：189-195页

核心收录：

学科分类：08[工学] 0825[工学-航空宇航科学与技术] 

基　　金：This work was supported by Innovative Funds of China Aerospace Science and Technology Cooperation 

主　　题：model error predictive estimation extended Kalman filter (EKF) attitude estimation. 

摘      要：A real-time attitude estimation algorithm, namely the predictive Kalman filter, is presented . This algorithm can accurately estimate the three-axis attitude of a satellite using only star sensor measurements. The implementation of the filter includes two steps: first, predicting the torque modeling error, and then estimating the attitude. Simulation results indicate that the predictive Kalman filter provides robust performance in the presence of both significant errors in the assumed model and in the initial conditions.