Analysis of the performance and sensitivity of eigendecomposition-based detectors

Author

Xu, Wenyuan ; Kaveh, Mostafa

Author_Institution

Dept. of Electr. Eng., Minnesota Univ., Minneapolis, MN, USA

Volume

43

Issue

6

fYear

1995

fDate

6/1/1995 12:00:00 AM

Firstpage

1413

Lastpage

1426

Abstract

A new framework is presented for the analysis of the performance of detection methods, such as AIC and MDL, which are based on the eigenvalues of the sample covariance matrix. It is shown that theoretical analysis of the probabilities of overestimation and underestimation can be much more conveniently carried out via a proposed, particularly simple, sequence of statistics. Also, the breakdown of these detection methods in the presence of model nonidealities is explored by theory, simulations, and experimentation with real array data. For example, theoretical arguments are given to demonstrate the high degree of sensitivity of the detectors to unknown deviations of the noise from whiteness

Keywords

Gaussian noise; array signal processing; covariance matrices; eigenvalues and eigenfunctions; information theory; maximum likelihood detection; probability; sensitivity analysis; signal sampling; AIC; MDL; array processsing; detection methods; eigendecomposition-based detectors; eigenvalues; experimentation; model nonidealities; noise whiteness deviations; overestimation probability; performance analysis; real array data; sample covariance matrix; sensitivity analysis; simulations; statistics; theoretical analysis; underestimation probability; unknown nonwhite Gaussian noise; Array signal processing; Calibration; Covariance matrix; Detectors; Eigenvalues and eigenfunctions; Electric breakdown; Performance analysis; Sensor arrays; Statistical analysis; Statistics;

fLanguage

English

Journal_Title

Signal Processing, IEEE Transactions on

Publisher

ieee

ISSN

1053-587X

Type

jour

DOI

10.1109/78.388854

Filename

388854