Multidimensional Low-Rank Filter based on the AU-HOSVD for MIMO STAP

Mélanie Boizard (1) , Frédéric Brigui (2) , Guillaume Ginolhac (3) , Frédéric Pascal (4) , Philippe Forster (1) , Hong Bo Sun (2)

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

We propose in this paper a new low rank filter for MIMO STAP (Multiple Input Multiple Output Space Time Adaptive Processing) based on the AU-HOSVD (Alternative Unfolding Higher Order Singular Value Decomposition). This decomposition called the AU-HOSVD is able to process data in correlated dimensions which is desirable for STAP methods. We apply the new filter to MIMO STAP simulated data. The results are encouraging and outperforms the conventional STAP 2D filter in terms of number of secondary data.

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

Mélanie Boizard, Frédéric Brigui, Guillaume Ginolhac, Frédéric Pascal, Philippe Forster, et al.. Multidimensional Low-Rank Filter based on the AU-HOSVD for MIMO STAP. 2013 IEEE 5th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP 2013) , Dec 2013, Saint Martin, France. pp.1-4, ⟨10.1109/CAMSAP.2013.6714095⟩. ⟨hal-00933556⟩