DocumentCode
1140724
Title
A new algorithm for state estimation of stochastic linear discrete systems
Author
Ahmed, M.S.
Author_Institution
Dept. of Syst. Eng., King Fahd Univ. of Pet. & Miner., Dhahran, Saudi Arabia
Volume
39
Issue
8
fYear
1994
fDate
8/1/1994 12:00:00 AM
Firstpage
1652
Lastpage
1656
Abstract
A novel algorithm is proposed for state estimation of linear discrete-time systems. The procedure performs explicit minimization of the innovation variance and is based upon the principle of pseudo linear regression (PLR) method. Sufficient conditions for algorithm convergence are also derived
Keywords
discrete time systems; estimation theory; filtering and prediction theory; minimisation; state estimation; statistical analysis; stochastic systems; algorithm convergence; innovation variance minimization; linear discrete-time systems; pseudo linear regression; state estimation; stochastic linear discrete systems; Convergence; Covariance matrix; Kalman filters; Linear regression; Minimization methods; Noise measurement; Riccati equations; State estimation; Stochastic systems; Technological innovation;
fLanguage
English
Journal_Title
Automatic Control, IEEE Transactions on
Publisher
ieee
ISSN
0018-9286
Type
jour
DOI
10.1109/9.310043
Filename
310043
Link To Document