DocumentCode :
850095
Title :
A quasi-linear estimation method--Application to Kalman filtering with stochastic regressors
Author :
RuskeepÄÄ, Heikki
Author_Institution :
University of Turku, Turku, Finland
Volume :
30
Issue :
8
fYear :
1985
fDate :
8/1/1985 12:00:00 AM
Firstpage :
767
Lastpage :
771
Abstract :
An estimation method, called quasi-linear estimation, is presented. Quasi-linear estimation is aimed to give an intermediate possibility between linear and nonlinear estimation. A quasi-linear estimator of a parameter vector a given two observation vectors y and z is defined to be of the form p + Qy , where the vector p and the matrix Q are \\sigma (z) -measurable. Orthogonal projections are used to derive the quasi-linear minimum mean square error estimator. This estimator is E(a|z) + C(a, y|z)V(y|z)-[y- E(y|z)] . Quasi-linear estimation is applied to derive a Kalman type filter for discrete-time dynamic linear models with stochastic regressors.
Keywords :
Kalman filtering, linear systems; Linear systems, stochastic; Nonlinear estimation; Parameter estimation; Stochastic systems, linear; Electrons; Equations; Filtering; Instruments; Kalman filters; Polynomials; Signal processing; Speech processing; Stochastic processes; System identification;
fLanguage :
English
Journal_Title :
Automatic Control, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9286
Type :
jour
DOI :
10.1109/TAC.1985.1104049
Filename :
1104049
Link To Document :
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