A robust signal subspace estimator
Arnaud Breloy, Yang Sun, Prabhu Babu, Guillaume Ginolhac, Daniel P. Palomar, Frédéric P. Pascal · 2016
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 Gaussian 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.