DocumentCode
3422864
Title
A statistical comparison between music and G-music
Author
Vallet, P. ; Loubaton, P. ; Mestre, X.
Author_Institution
Lab. IMS, Univ. Bordeaux, Talence, France
fYear
2015
fDate
19-24 April 2015
Firstpage
2829
Lastpage
2833
Abstract
This paper addresses the statistical performance of subspace DoA estimation using a sensor array, in the asymptotic regime where the number of samples and sensors both converge to infinity at the same rate. Improved subspace DoA estimators were derived (termed as G-MUSIC) in previous works, and were shown to be consistent and asymptotically Gaussian distributed in the case where the number of sources and their DoA remain fixed. In this case, which models widely spaced DoA scenarios, it is established that the traditional MUSIC method also provides consistent DoA estimates having the same asymptotic MSE as the G-MUSIC estimates. In the case of closely spaced DoA (i.e. with a spacing of the order of a beamwidth), it is shown that G-MUSIC is still able to consistently separate the sources, while it is no longer the case for MUSIC.
Keywords
Gaussian distribution; direction-of-arrival estimation; mean square error methods; signal classification; G-MUSIC; MUSIC; a sensor array; asymptotic MSE; asymptotic regime; sample number convergence; sensor number convergence; statistical comparison; subspace DoA estimation; Signal to noise ratio; DoA estimation; MUSIC; consistency;
fLanguage
English
Publisher
ieee
Conference_Titel
Acoustics, Speech and Signal Processing (ICASSP), 2015 IEEE International Conference on
Conference_Location
South Brisbane, QLD
Type
conf
DOI
10.1109/ICASSP.2015.7178487
Filename
7178487
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