Wideband multiple diversity tensor array processing

Francesca Raimondi (1) , Rodrigo Cabral Farias (2) , Olivier J.J. Michel (1) , Pierre Comon (1)

1 GIPSA-CICS - GIPSA - Communication Information and Complex Systems
2 Laboratoire d'Informatique, Signaux, et Systèmes de Sophia-Antipolis (I3S) / Equipe SYSTEMES

This paper establishes a tensor model for wideband coherent array processing including multiple physical diversities. A separable coherent focusing operation is proposed as a pre-processing step in order to ensure the multilinearity of the interpolated data. We propose an ALS algorithm to process tensor data, taking into account the noise correlation structure introduced by the focusing operation. We show through computer simulations that the estimation of DoA and polarization parameters improves compared to existing narrowband tensor processing and wideband MUSIC. The performance is also compared to the Cramér-Rao bounds of the wideband tensor model.

Mots clés: MUSIC; CP decomposition; polarization; tensor; localization; DoA estimation; interpolation; wideband; antenna array processing; High Resolution

Domaines: Traitement du signal et de l'image [eess.SP]; Théorie de l'information [cs.IT]; Algorithme et structure de données [cs.DS]

Francesca Raimondi, Rodrigo Cabral Farias, Olivier J.J. Michel, Pierre Comon. Wideband multiple diversity tensor array processing. IEEE Transactions on Signal Processing, 2017, 65 (20), pp.5334-5346. ⟨10.1109/TSP.2017.2725219⟩. ⟨hal-01350549v5⟩