In recent years, the Kalman filter based on the minimum error entropy (MEE) criterion has been proposed, which outperforms the traditional Kalman filter in the presence of non-Gaussian noise. In practical applications, the estimated performance of the MEE unscented Kalman filter (MEE-UKF) algorithm is influenced by the kernel bandwidth (KB). In addition, it may be unstable in numerical computation. This paper proposes an adaptive robust MEE unscented Kalman filter (AMEE-UKF) to address the problem of instability in numerical computation. In addition, by setting an adaptive factor to optimize the MEE-UKF, an appropriate value of the KB can be obtained adaptively. The high accuracy and robustness of the AMEE-UKF were demonstrated by the simulation experiments.


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    Title :

    Adaptive Robust Minimum Error Entropy Unscented Kalman Filter for Satellite Attitude Estimation


    Additional title:

    J. Aerosp. Eng.


    Contributors:
    Qian, Huaming (author) / Chu, Shuai (author) / Zhao, Di (author)

    Published in:

    Publication date :

    2022-09-01




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



    Residual Based Adaptive Unscented Kalman Filter for Satellite Attitude Estimation

    Soken, H. / Sakai, S.-i. / American Institute of Aeronautics and Astronautics | British Library Conference Proceedings | 2012