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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    Title :

    Applications of Mininum Variance Reduced-State Estimators


    Contributors:

    Published in:

    Publication date :

    1975-09-01


    Size :

    2388690 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English