• 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