This article presents a Kalman-type recursive estimator for discrete-time systems with a measurement noise modeled by a Gaussian-uniform mixture. The objective is to deal with data containing outliers that degrade the performance of the regular Kalman filter. The proposed non-Gaussian noise model takes into account the reliability of the measurement with respect to erroneous data. The Kalman-type estimator is based on Masreliez's formulation which copes with non-Gaussian noise models. Results in different simulated conditions are displayed to evaluate the performance of the newly-presented algorithm and to compare it to state-of-art alternatives.


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    Titel :

    A Gaussian Uniform Mixture Model for Robust Kalman Filtering


    Beteiligte:


    Erscheinungsdatum :

    01.08.2020


    Format / Umfang :

    1719688 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch





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