Applications of Mininum Variance Reduced-State Estimators
Christopher R. Hutchinson, Joseph A. D'Appolito, Kallol Roy · IEEE Transactions on Aerospace and Electronic Systems · 1975
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.