Noise Power Gain for Discrete-Time FIR Estimators

Author

Shmaliy, Yuriy S. ; Ibarra-Manzano, Oscar

Author_Institution

Dept. of Electron., Guanajuato Univ., Salamanca, Mexico

Volume

18

Issue

4

fYear

2011

fDate

4/1/2011 12:00:00 AM

Firstpage

207

Lastpage

210

Abstract

The noise power gain (NPG) matrix is specialized in state space for transversal finite impulse response (FIR) estimators intended for filtering, prediction, and smoothing of discrete time-variant K-state models with M states measured. A computationally efficient iterative algorithm for NPG associated with unbiased estimation is provided along. Based on a numerical example, we show that the estimates are well bounded with the error bound (EB) specified in the three-sigma sense by the main components of the NPG matrix and measurement noise variance. In turn, the cross-components in the NPG matrix represent interactions in the estimator channels. It is concluded that EB can serve as an efficient measure of errors in optimal and suboptimal FIR and Kalman structures.

Keywords

FIR filters; Kalman filters; discrete time filters; estimation theory; iterative methods; matrix algebra; prediction theory; smoothing methods; state-space methods; Kalman structures; NPG matrix; computationally efficient iterative algorithm; cross-components; discrete time-variant K-state models; discrete-time FIR estimators; error bound; estimator channels; filtering; measurement noise variance; noise power gain; prediction; smoothing; state space; three-sigma sense; transversal finite impulse response estimators; unbiased estimation; Error bound; FIR estimator; noise power gain; state space;

fLanguage

English

Journal_Title

Signal Processing Letters, IEEE

Publisher

ieee

ISSN

1070-9908

Type

jour

DOI

10.1109/LSP.2011.2108647

Filename

5701759