Expected likelihood-based detection-estimation of multirank signals

Author

Abramovich, Y.I. ; Johnson, B.A. ; Scharf, L.L. ; Pezeshki, A. ; Spencer, N.K.

Author_Institution

ISRD, Defence Sci. & Technol. Organ. (DSTO), Edinburgh, SA, Australia

fYear

2009

fDate

1-4 Nov. 2009

Firstpage

469

Lastpage

471

Abstract

Even for the simple rank-one plane-wave model, the accurate maximum-likelihood (ML) solution of the detection-estimation problem is infeasible, mainly because the multivariate likelihood function is non-convex and multi-extremal. For this reason, a number of "ML-proxy" routines have been developed that, in some important practical cases, approach the efficiency of the ML performance benchmark (Cramer-Rao bound, CRB), for sufficiently large sample volume T and/or signal-to-noise ratio (SNR).

Keywords

maximum likelihood detection; Cramer-Rao bound; ML-proxy; SNR; expected likelihood-based detection-estimation; maximum-likelihood solution; multirank signal; multivariate likelihood function; rank-one plane-wave model; signal-to-noise ratio; Covariance matrix; Direction of arrival estimation; Maximum likelihood estimation; Multiple signal classification; Radar applications; Radar imaging; Sensor arrays; Signal detection; Sonar; Training data;

fLanguage

English

Publisher

ieee

Conference_Titel

Signals, Systems and Computers, 2009 Conference Record of the Forty-Third Asilomar Conference on

Conference_Location

Pacific Grove, CA

ISSN

1058-6393

Print_ISBN

978-1-4244-5825-7

Type

conf

DOI

10.1109/ACSSC.2009.5469864

Filename

5469864