A higher-order robust correlation Kalman filter for satellite attitude estimation. (May 2022)

• Record Type: Journal Article
• Authors: Chen, Xiaoqian; Cao, Lu; Guo, Pengyu; Xiao, Bing
• Is Part Of: ISA transactions. Volume 124(2022)
• Page Start: 326
• Page End: 337
• Publication Date: 2022-05
• Subjects: Satellite -- Attitude estimation -- Sigma point -- Modeling error -- High-order filter; Engineering instruments -- Periodicals; Engineering instruments; Periodicals; Electronic journals; 629.805
• DOI: 10.1016/j.isatra.2019.12.009
• Languages: English
• ISSNs: 0019-0578

Abstract

Abstract: A higher-order robust correlation Kalman filtering approach is presented to achieve attitude estimation for satellites with unknown modeling errors. A robust correlation Kalman filter (RCKF) is preliminarily derived by using the sequence orthogonal principle. To improve its performance further, a higher-order sigma version of the RCKF is designed by incorporating a novel sigma point generation algorithm. This modified filter can capture the third and the fourth central moment's information of the system posteriori probability density function. It is proved that the proposed filter achieves better estimation accuracy and robustness. The effectiveness of the developed filter is demonstrated by simulation results with it applied to the satellite attitude estimation problem.