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 Q and the output noise covariance R 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 \\Gamma directly without the intermediate determination of the unknown covariances Q and R . 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
Link To Document :
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