DocumentCode :
827437
Title :
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
Link To Document :
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