A new information formulation of the Kalman filter is presented where the information matrix is parameterized as the product of an upper triangular matrix, a diagonal matrix, and the transpose of a triangular matrix (referred as UDU factorization). The UDU factorization of the Kalman filter is known for its numerical stability; this paper extends the technique to the information filter. A distinct characteristic of the new algorithm is that measurements can be processed as vectors, while the classic UDU factorization requires scalar measurement processing, i.e., a diagonal measurement noise covariance matrix.


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    Titel :

    Information Formulation of the UDU Kalman Filter


    Beteiligte:


    Erscheinungsdatum :

    01.02.2019


    Format / Umfang :

    939755 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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