Robust estimation of the clutter subspace for a Low Rank heterogeneous noise under high Clutter to Noise Ratio assumption

Arnaud Breloy (1) , Guillaume Ginolhac (2) , Frédéric Pascal (3) , Philippe Forster (1)

1 SATIE - Systèmes et Applications des Technologies de l'Information et de l'Energie
2 LISTIC - Laboratoire d'Informatique, Systèmes, Traitement de l'Information et de la Connaissance
3 SONDRA - Sondra, CentraleSupélec, Université Paris-Saclay (COmUE)

In the context of an heterogeneous disturbance with a Low Rank (LR) structure (called clutter), one may use the LR approximation for filtering and detection process. These methods are based on the projector onto the clutter subspace instead of the noise covariance matrix. In such context, adaptive LR schemes have been shown to require less secondary data to reach equivalent performances as classical ones. The main problem is then the estimation of the clutter subspace instead of the noise covariance matrix itself. Maximum Likelihood estimator (MLE) of the clutter subspace has been recently studied for a noise composed of a LR Spherically Invariant Random Vector (SIRV) plus a white Gaussian Noise (WGN). This paper focuses on environments with a high Clutter to Noise Ratio (CNR). An original MLE of the clutter subspace is proposed in this context. A cross-interpretation of this new result and previous ones is provided. Validity and interest - in terms of performance and robustness - of the different approaches are illustrated through simulation results.

Domaines: Traitement du signal et de l'image [eess.SP]; Traitement du signal et de l'image [eess.SP]

Arnaud Breloy, Guillaume Ginolhac, Frédéric Pascal, Philippe Forster. Robust estimation of the clutter subspace for a Low Rank heterogeneous noise under high Clutter to Noise Ratio assumption. 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2014), May 2014, Florence, Italy. pp.1-5, ⟨10.1109/ICASSP.2014.6853559⟩. ⟨hal-01024200⟩