Wideband multiple diversity tensor array processing

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

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