Numerical performances of low rank stap based on different heterogeneous clutter subspace estimators

Arnaud Breloy (1) , G Ginolhac (2) , F Pascal (3) , P 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)

Space time Adaptive Processing (STAP) for airborne RADAR fits the context of a disturbance composed of a Low Rank (LR) clutter, here modeled by a Compound Gaussian (CG) process, plus a white Gaussian noise (WGN). In such context, the corresponding LR adaptive filters used to detect a target require less training vectors than classical methods to reach equivalent performance. Unlike the classical filter which is based on the Covariance Matrix (CM) of the noise, the LR filter is based on the clutter subspace projector, which is usually derived from a Singular Value Decomposition (SVD) of a noise CM estimate. Regarding to the considered model of LR-CG plus WGN, recent results are providing both direct estimators of the clutter subspace [1][2] and an exact MLE of the noise CM [3]. To promote the use of these new estimation methods, this paper proposes to apply them to realistic STAP simulations.

Mots clés: Covariance Matrix and Projector esti-mation; Maximum Likelihood Estimator; Low-Rank clutter; SIRV; STAP

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

Arnaud Breloy, G Ginolhac, F Pascal, P Forster. Numerical performances of low rank stap based on different heterogeneous clutter subspace estimators. 2014 International Radar Conference , Oct 2014, Lille, France. ⟨10.1109/RADAR.2014.7060426⟩. ⟨hal-01084418⟩