• DocumentCode
    2056846
  • Title

    On the resolution probability of conditional and unconditional maximum likelihood DOA estimation

  • Author

    Mestre, Xavier ; Vallet, Pascal ; Loubaton, P.

  • Author_Institution
    Centre Tecnol. de Telecomunicacions de Catalunya, Barcelona, Spain
  • fYear
    2013
  • fDate
    9-13 Sept. 2013
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    The outlier production mechanism of maximum likelihood direction-of-arrival estimators is investigated. The objective is to provide an accurate description of the probability of resolution for both conditional and unconditional maximum likelihood methods in the small sample size regime. To that effect, the asymptotic behavior of these two cost functions is analyzed assuming that both the number of antennas and the number of available snapshots increase without bound at the same rate, so that both quantities are comparable in magnitude. The finite dimensional distributions of both conditional and unconditional cost functions are shown to be Gaussian in this asymptotic regime, and a closed form expression of the corresponding asymptotic covariance matrices is provided.
  • Keywords
    Gaussian processes; covariance matrices; direction-of-arrival estimation; maximum likelihood estimation; signal processing; Gaussian processes; antennas; asymptotic behavior; asymptotic covariance matrices; direction-of-arrival; finite dimensional distributions; outlier production mechanism; resolution probability; sample size regime; snapshots; unconditional cost functions; unconditional maximum likelihood DOA estimation; Arrays; Cost function; Direction-of-arrival estimation; Maximum likelihood estimation; Unified modeling language; Vectors; Conditional ML; DoA estimation; Unconditional ML; central limit theorem; random matrix theory;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing Conference (EUSIPCO), 2013 Proceedings of the 21st European
  • Conference_Location
    Marrakech
  • Type

    conf

  • Filename
    6811568