On the High-SNR Conditional Maximum-Likelihood Estimator Full Statistical Characterization

Author

Renaux, Alexandre ; Forster, Philippe ; Chaumette, Eric ; Larzabal, Pascal

Author_Institution

SATIE Lab., Ecole Normale Superieure de Cachan

Volume

54

Issue

12

fYear

2006

Firstpage

4840

Lastpage

4843

Abstract

In the field of asymptotic performance characterization of the conditional maximum-likelihood (CML) estimator, asymptotic generally refers to either the number of samples or the signal-to-noise ratio (SNR) value. The first case has been already fully characterized, although the second case has been only partially investigated. Therefore, this correspondence aims to provide a sound proof of a result, i.e., asymptotic (in SNR) Gaussianity and efficiency of the CML estimator in the multiple parameters case, generally regarded as trivial but not so far demonstrated

Keywords

Gaussian processes; array signal processing; maximum likelihood estimation; asymptotic Gaussianity; asymptotic performance characterization; full statistical characterization; high-SNR conditional maximum-likelihood estimator; signal-to-noise ratio; Array signal processing; Gaussian processes; Maximum likelihood estimation; Radar antennas; Radar signal processing; Sensor arrays; Signal processing; Signal processing algorithms; Signal to noise ratio; Stochastic processes; Array processing; high signal-to-noise ratio (SNR); maximum likelihood; statistical efficiency;

fLanguage

English

Journal_Title

Signal Processing, IEEE Transactions on

Publisher

ieee

ISSN

1053-587X

Type

jour

DOI

10.1109/TSP.2006.882072

Filename

4014393