According to Kalman filtering for strapdown inertial navigation based integrated navigation, the measurement often has interference. The interference can reduce the effect of filtering estimation. In this paper, a robust sequential Kalman filtering algorithm based on Huber is proposed. The algorithm combines sequential Kalman and Huber. In numerical experiments, the estimation of the robust sequential Kalman filter and the Kalman filter are compared under the presence of pollution in the measurement. The results show that the robust sequential Kalman filtering algorithm has strong anti-interference capability.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Robust sequential Kalman filter for inertial integrated


    Beteiligte:
    Xin, Lu (Autor:in) / Bai-qing, Hu (Autor:in) / Guang-jun, Zhang (Autor:in) / Bo-yang, Xue (Autor:in)


    Erscheinungsdatum :

    01.08.2018


    Format / Umfang :

    466882 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




    Robust Visual-Inertial Odometry Based on a Kalman Filter and Factor Graph

    Wang, Zhiwei / Pang, Bao / Song, Yong et al. | IEEE | 2023


    Quaternion Kalman filter for inertial measurement units

    Escobar, Jossue Carino / Cabarbaye, Aurelien / Estrada, Moises Bonilla et al. | IEEE | 2017