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Steady‐state Kalman filtering with nonstationary noise
Author(s) -
Mäkilä P. M.,
Paattilammi J.
Publication year - 2003
Publication title -
optimal control applications and methods
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.458
H-Index - 44
eISSN - 1099-1514
pISSN - 0143-2087
DOI - 10.1002/oca.720
Subject(s) - kalman filter , covariance , mathematics , ergodic theory , noise (video) , covariance matrix , computer science , mathematical analysis , algorithm , statistics , artificial intelligence , image (mathematics)
Infinite‐horizon Kalman filtering is re‐examined for linear discrete‐time systems and generalized to include a class of non‐stationary and non‐ergodic disturbances. This revision is achieved by defining a generalized infinite‐horizon filtering problem using a flexible functional analytic signal description. It is shown that the solution to the generalized filtering problem is equivalent to the solution of the corresponding standard filtering problem with noise covariance matrices having in the generalized problem a different, more general, meaning than in the standard problem. In the generalized problem these covariance matrices are majorizing matrices that have a precise meaning even in the non‐stationary and non‐ergodic signal case. This result justifies in a nice way the wide practice of interpreting the noise covariance matrices in Kalman filtering as design variables. Copyright © 2003 John Wiley & Sons, Ltd.