期刊
IEEE TRANSACTIONS ON SIGNAL PROCESSING
卷 56, 期 9, 页码 4113-4123出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSP.2008.926101
关键词
constrained gain; Kalman filter; state estimation; unscented Kalman filter
This paper considers the state-estimation problem with it constraint on the data-injection gain. Special cases of this problem include the enforcing of a linear equality constraint in the state vector, the enforcing of unbiased estimation for systems with unknown inputs, and simplification of the estimator structure for large-scale systems. Both the one-step gain-constrained Kalman predictor and the two-step gain-constrained Kalman filter are presented. The latter is extended to the nonlinear case, yielding the gain-constrained unscented Kalman filter. Two illustrative examples are presented.
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