DocumentCode
813217
Title
Identification of optimum filter steady-state gain for systems with unknown noise covariances
Author
Carew, Burian ; Belanger, Pierre R.
Author_Institution
McGill University, Montreal, Canada
Volume
18
Issue
6
fYear
1973
fDate
12/1/1973 12:00:00 AM
Firstpage
582
Lastpage
587
Abstract
A discrete linear stationary system is considered for which the input noise covariance
and the output noise covariance
are unknown. A stable filter with a suboptimal gain is assumed. An identification scheme is presented which uses the autocorrelation functions of the innovations sequence of the suboptimal filter to determine the optimum filter steady state gain
directly without the intermediate determination of the unknown covariances
and
. The approach used is to identify an output equivalent representation of the original system which does not involve the unknown covariances directly.
and the output noise covariance
are unknown. A stable filter with a suboptimal gain is assumed. An identification scheme is presented which uses the autocorrelation functions of the innovations sequence of the suboptimal filter to determine the optimum filter steady state gain
directly without the intermediate determination of the unknown covariances
and
. The approach used is to identify an output equivalent representation of the original system which does not involve the unknown covariances directly.Keywords
Innovations methods; Linear systems, stochastic discrete-time; State estimation; Autocorrelation; Equations; Hafnium; Kalman filters; Nonlinear filters; Observability; Steady-state; Technological innovation; Variable speed drives;
fLanguage
English
Journal_Title
Automatic Control, IEEE Transactions on
Publisher
ieee
ISSN
0018-9286
Type
jour
DOI
10.1109/TAC.1973.1100420
Filename
1100420
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