This paper presents an algorithm for a class of suitably constrained reduced-order filters which minimize the variance of the estimated variables. The algorithm generates both the filter gain history and the true estimation error covariance. The algorithm provides a quantitative criterion which can be used to measure the performance of any reduced-order estimator. Both continuous and discrete estimators are considered. Several examples are treated including an application of the technique to a hybrid navigation system of high order.


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    Titel :

    Applications of Mininum Variance Reduced-State Estimators


    Beteiligte:
    Hutchinson, C. E. (Autor:in) / D'Appolito, J.A. (Autor:in) / Roy, K.J. (Autor:in)

    Erschienen in:

    Erscheinungsdatum :

    01.09.1975


    Format / Umfang :

    2388690 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch