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    Source enumeration in large arrays using moments of eigenvalues and relatively few samples

    , Article IET Signal Processing ; Volume 6, Issue 7 , 2012 , Pages 689-696 ; 17519675 (ISSN) Yazdian, E ; Gazor, S ; Bastani, H ; Sharif University of Technology
    IET  2012
    Abstract
    This study presents a method based on minimum description length criterion to enumerate the incident waves impinging on a large array using a relatively small number of samples. The proposed scheme exploits the statistical properties of eigenvalues of the sample covariance matrix (SCM) of Gaussian processes. The authors use a number of moments of noise eigenvalues of the SCM in order to separate noise and signal subspaces more accurately. In particular, the authors assume a Marcenko-Pastur probability density function (pdf) for the eigenvalues of SCM associated with the noise subspace. We also use an enhanced noise variance estimator to reduce the bias leakage between the subspaces....