Performance evaluation of an ARMA estimator

Author

Zerubia, Josiane ; Alengrin, Gérard ; Rix, Hervd

Author_Institution

Nice Univ., France

fYear

1988

fDate

11-14 Apr 1988

Firstpage

2424

Abstract

The authors study the asymptotic error variance of the ARMA (autoregressive moving-average) parameters. The ARMA estimation method involves a two-step procedure: first, the AR parameters are estimated using the Burg algorithm and the time-varying components of a Kalman filter gain. Then the MA parameters are obtained using a fast identification algorithm derived from Chandrasekhar equations. The authors report on results obtained for some very simple examples: ARMA (2,2) and ARMA (4,4). They study the influence of the SNR, the process bandwidth, and the length of the observation window

Keywords

Kalman filters; filtering and prediction theory; parameter estimation; signal processing; ARMA estimator; Burg algorithm; Chandrasekhar equations; Kalman filter; SNR; asymptotic error variance; autoregressive moving-average; fast identification algorithm; observation window length; parameter estimation; process bandwidth; signal processing; Equations; Kalman filters; Parameter estimation; Poles and zeros; Polynomials; Predictive models; Signal processing algorithms; Signal to noise ratio; Transfer functions; White noise;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech, and Signal Processing, 1988. ICASSP-88., 1988 International Conference on

Conference_Location

New York, NY

ISSN

1520-6149

Type

conf

DOI

10.1109/ICASSP.1988.197131

Filename

197131