Linear smoothing for discrete-time systems in the presence of correlated disturbances and uncertain observations

Author

Carazo, A. Hermoso ; Pérez, J. Linares

Author_Institution

Dept. de Estadistica e Investigacion, Granada Univ., Spain

Volume

40

Issue

8

fYear

1995

fDate

8/1/1995 12:00:00 AM

Firstpage

1486

Lastpage

1488

Abstract

This paper considers the smoother with the least mean-squared error (LMSE) within the class of linear smoothers for discrete linear systems whose observations may contain noise alone and the probability of this occurring is known (systems with uncertain observations). Also, we assume that state and measurement noises are correlated. The present results, together with Hermoso-Linares´s results on prediction and filtering, give a complete treatment of the LMSE linear estimation problem for such systems

Keywords

discrete time systems; error statistics; least mean squares methods; linear systems; prediction theory; probability; smoothing methods; uncertain systems; Hermoso-Linares approach; correlated disturbances; discrete-time systems; filtering; least mean-squared error; linear smoothing; linear systems; measurement noise; prediction; probability; state noise; uncertain observations; Equations; Linear systems; Noise measurement; Nonlinear filters; Random variables; Recursive estimation; Smoothing methods; State estimation; Vectors; White noise;

fLanguage

English

Journal_Title

Automatic Control, IEEE Transactions on

Publisher

ieee

ISSN

0018-9286

Type

jour

DOI

10.1109/9.402248

Filename

402248