To solve the problem of unknown noise covariance matrices inherent in the cooperative localization of autonomous underwater vehicles, a new adaptive extended Kalman filter is proposed. The predicted error covariance matrix and measurement noise covariance matrix are adaptively estimated based on an online expectation-maximization approach. Experimental results illustrate that, under the circumstances that are detailed in the paper, the proposed algorithm has better localization accuracy than existing state-of-the-art algorithms.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    A New Adaptive Extended Kalman Filter for Cooperative Localization


    Beteiligte:
    Yulong Huang (Autor:in) / Yonggang Zhang (Autor:in) / Bo Xu (Autor:in) / Zhemin Wu (Autor:in) / Chambers, Jonathon A. (Autor:in)


    Erscheinungsdatum :

    01.02.2018


    Format / Umfang :

    1691046 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch