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.


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    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 :

    2018-02-01


    Format / Umfang :

    1691046 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch