• DocumentCode
    2812453
  • Title

    MUSIC-Based Joint DoA Estimation and Signal Enumeration

  • Author

    Wu, Ren ; Psaromiligkos, Ioannis N.

  • Author_Institution
    McGill Univ., Montreal
  • fYear
    2007
  • fDate
    22-26 April 2007
  • Firstpage
    1030
  • Lastpage
    1033
  • Abstract
    In this paper we describe a new criterion for the detection of the number of signals impinging on a M-element uniform linear array (ULA). Our criterion makes explicit use of the peak information of the MUSIC spectrum. Specifically, for each hypothesis of k sources, in addition to computing the noise variance estimate using the M-k smallest eigenvalues of the sample covariance matrix, the new criterion applies an additional correction term calculated from the k largest peaks of the MUSIC spectrum which is generated from the testing noise subspace of dimension M-k. We prove that the proposed criterion provides a consistent estimate of the number of signals and demonstrate that it has a better performance at low SNR for equal-power sources when compared with the original MDL-based signal number detection criterion [1]. Enumeration Ren Wu and Ioannis N. Psaromiligkos
  • Keywords
    covariance matrices; direction-of-arrival estimation; eigenvalues and eigenfunctions; signal detection; MUSIC spectrum; covariance matrix; eigenvalues; signal detection; signal enumeration; uniform linear array; Array signal processing; Covariance matrix; Direction of arrival estimation; Eigenvalues and eigenfunctions; Multiple signal classification; Noise generators; Signal detection; Signal to noise ratio; Testing; Vectors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electrical and Computer Engineering, 2007. CCECE 2007. Canadian Conference on
  • Conference_Location
    Vancouver, BC
  • ISSN
    0840-7789
  • Print_ISBN
    1-4244-1020-7
  • Electronic_ISBN
    0840-7789
  • Type

    conf

  • DOI
    10.1109/CCECE.2007.263
  • Filename
    4232922