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• W2022953248 abstract "In derivations of the Kalman-Bucy filter, one generally assumes that the measurement noise process possesses a nonsingular covariance matrix. Some authors, [1], [2], have derived formulas for a reduced order optimal estimator with a singular covariance matrix. Their solutions require coordinate transformations in both state and output noise variables. Here we employ the Moore-Penrose generalized inverse of the noise covariance matrix to obtain a full order optimal filter without the use of coordinate transformations. Two different optimal estimators corresponding to two different optimization criteria are found. One of these estimators provides a duality principle relating the optimal estimation problem with a partially singular optimal control problem." @default.
• W2022953248 created "2016-06-24" @default.
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• W2022953248 date "1981-12-01" @default.
• W2022953248 modified "2023-09-24" @default.
• W2022953248 title "A duality principle for state estimation with partially noise corrupted measurements" @default.
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• W2022953248 doi "https://doi.org/10.1109/cdc.1981.269283" @default.
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