학술논문
Polynomial filtering of systems with non-independent uncertain observations
Document Type
Conference
Author
Source
2004 43rd IEEE Conference on Decision and Control (CDC) (IEEE Cat. No.04CH37601) Decision and control Decision and Control, 2004. CDC. 43rd IEEE Conference on. 3:3109-3114 2004
Subject
Language
ISSN
0191-2216
Abstract
The filtering problem for non-Gaussian, discretetime, linear systems with correlated uncertainty in the observation equation is investigated in the present paper. A stochastic Markov sequence of correlated Bernoulli random variables is considered as a model for the uncertainty in the measurements. For this class of systems Hadidi-Schwartz defined a linear filter (giving the linear-optimal state estimate) assuming some structural properties of the system are satisfied. In the present paper similar conditions are shown to imply the existence of a polynomial filter (of any degree). Finally, the general polynomial filter equations are derived for the considered class of systems.