The noise is easily impacted by outliers in the complex space environment. In this case, the filtering accuracy of the classical central difference Kalman filter (CDKF) will decrease. To enhance the robustness of the CDKF, the robust centered error entropy central difference Kalman filter (CEECDKF) is derived. The proposed CEECDKF algorithm uses Stirling interpolation for nonlinear transfer of random variables and the posterior state estimation values are got by the CEE criterion. Different from the classic CDKF algorithm, the CEE criterion is not sensitive to outliers. The developed algorithm is applied to the spacecraft attitude estimation system with non-Gaussian noise and the filtering results verify its validity.
Centered Error Entropy Based Central Difference Kalman Filter for Nanosatellite Attitude Estimation
Lect. Notes Electrical Eng.
International Conference on Autonomous Unmanned Systems ; 2021 ; Changsha, China September 24, 2021 - September 26, 2021
Proceedings of 2021 International Conference on Autonomous Unmanned Systems (ICAUS 2021) ; Chapter : 306 ; 3122-3132
2022-03-18
11 pages
Article/Chapter (Book)
Electronic Resource
English
Extended Kalman Filter vs. Error State Kalman Filter for Aircraft Attitude Estimation
British Library Conference Proceedings | 2011
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