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.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

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


    Weitere Titelangaben:

    J. Aerosp. Eng.


    Beteiligte:
    Qian, Huaming (Autor:in) / Chu, Shuai (Autor:in) / Zhao, Di (Autor:in)

    Erschienen in:

    Erscheinungsdatum :

    2022-09-01




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    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



    Robust double gain unscented Kalman filter for small satellite attitude estimation

    Cao, Lu / Yang, Weiwei / Li, Hengnian et al. | Elsevier | 2017