Signal Processing 2019 DOI: 10.1016/j.sigpro.2019.06.017 View full text
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Habti Abeida, Jean Pierre Delmas

Abstract: This paper addresses the theoretical analysis of the robustness of subspace-based algorithms with respect to non-Gaussian noise distributions using perturbation expansions. Its purpose is twofold. It aims, first, to derive the asymptotic distribution of the estimated projector matrix obtained from the sample covariance matrix (SCM) for arbitrary distributions of the useful signal and the noise. It proves that this distribution depends only of the second-order statistics of the useful signal, but also on the se…

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