A robust signal subspace estimator
Résumé
An original estimator of the orthogonal projector onto the signal subspace is proposed. This estimator is derived as the maximum likelihood estimator for a model of sources plus orthogonal outliers, both with varying power (modeled by Compound Gaussians process), embedded in a white Gaus-sian noise. Validity and interest-in terms of performance and robustness-of this estimator is illustrated through simulation results on a low rank STAP filtering application.
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