The Unified Structure of Unbiased Minimum-Variance Reduced-Order Filters

Author

Hsieh, Chien-Shu

Author_Institution

Ta Hwa Inst. of Technol., Hsinchu

Volume

52

Issue

9

fYear

2007

Firstpage

1716

Lastpage

1721

Abstract

A unified two-stage functional filter (UTSFF) is proposed, serving as a unified structure of unbiased minimum-variance reduced-order filters for linear time-varying discrete-time systems. The UTSFF includes two parts: one is for the main functional estimate, which defines the main computing structure of the filter, and the other is for the complementary functional estimate, which is added to the former in order to further enhance the filtering performance. The relationships between the UTSFF and existing reduced-order filters are explored. Through the UTSFF, a general procedure for applying a suitable unbiased minimum-variance reduced-order filter is given. Simulation examples are also given to illustrate the proposed results.

Keywords

discrete time systems; filtering theory; linear systems; reduced order systems; time-varying systems; linear time-varying discrete-time systems; unbiased minimum-variance reduced-order filters; unified structure; unified two-stage functional filter; Computational complexity; Filtering; Kalman filters; Noise measurement; Noise reduction; Nonlinear filters; State estimation; Stochastic systems; Time varying systems; Vectors; Estimation; functional filter; reduced order filtering; two-stage Kalman filtering; unbiased minimum-variance filter;

fLanguage

English

Journal_Title

Automatic Control, IEEE Transactions on

Publisher

ieee

ISSN

0018-9286

Type

jour

DOI

10.1109/TAC.2007.904286

Filename

4303230