DocumentCode
846960
Title
The properties of reduced-order minimum-variance filters for systems with partially perfect measurements
Author
Soroka, Eugene ; Shaked, Uri
Author_Institution
Israel Aircraft Ind. Ltd., Lod, Israel
Volume
33
Issue
11
fYear
1988
Firstpage
1022
Lastpage
1034
Abstract
The problem of the finite-time, reduced-order, minimum variance full-state estimation of linear, continuous time-invariant systems is considered in cases where the output measurement is partially free of corrupting white-noise components. The structure of the optimal filter is obtained and a link between this structure and the structure of the system invariant zeros is established. Using expressions that are derived in closed form for the invariant zeros of the system, simple sufficient conditions are obtained for the existence of the optimal filter in the stationary case. The structure and the transmission properties of the stationary filter for general left-invertible systems are investigated. A direct relation between the optimal filter and a particular minimum-order left inverse of the system is obtained. A simple explicit expression for the filter transfer function matrix is also derived. The expression provides an insight into the mechanism of the optimal estimation.<>
Keywords
State estimation; filtering and prediction theory; linear systems; matrix algebra; poles and zeros; state estimation; transfer functions; continuous systems; full-state estimation; general left-invertible systems; invariant zeros; linear systems; optimal estimation; optimal filter; partially perfect measurements; reduced-order minimum-variance filters; state estimation; time-invariant systems; transfer function matrix; transmission properties; Filtering; Noise measurement; Nonlinear filters; State estimation; Sufficient conditions; Time domain analysis; Transfer functions; Vectors; White noise; Yield estimation;
fLanguage
English
Journal_Title
Automatic Control, IEEE Transactions on
Publisher
ieee
ISSN
0018-9286
Type
jour
DOI
10.1109/9.14414
Filename
14414
Link To Document