Adaptive Kalman filtering for spacecraft attitude estimation

被引：0

作者：

Li, Wei ^{[1
]}

Liu, Meihong ^{[1
]}

Gong, Deren ^{[1
]}

Duan, Dengping ^{[1
]}

机构：

[1] Institute of Aerospace Science and Technology, Shanghai Jiao Tong University, Shanghai 200240, Rm. 2115, Aerospace Building, No. 800, Dongchuan Road

来源：

Journal of Aeronautics, Astronautics and Aviation | 2013年 / 45卷 / 01期

关键词：

Adaptive Kalman filter; Attitude estimation; Spacecraft;

D O I：

10.6125/12-1112-713

中图分类号：

学科分类号：

摘要：

An adaptive Kalman filter (AKF) algorithm is proposed to model and approximation errors in this work. The adaptive algorithm for model and approximation errors is attained by using an upper bound for the state error prediction covariance matrix. The proposed adaptive filter algorithm has been tested in attitude estimation using gyroscope and star tracker sensors for single spacecraft in flight simulations. Simulation results demonstrate the superior performance of the proposed filter as compared to the standard Kalman filter.

引用

页码：45 / 50

页数：5

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