Wideband Multiple Diversity Tensor Array Processing
Francesca Raimondi, Rodrigo Cabral Farias, Olivier Michel, Pierre Comon · IEEE Transactions on Signal Processing · 2017
This paper establishes a tensor model for wideband coherent array processing including multiple physical diversities. A separable coherent focusing operation is proposed as a preprocessing step in order to ensure the multilinearity of the interpolated data. We propose an alternating least squares 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 direction of arrival and polarization parameters improves compared to existing narrowband tensor processing and wideband MUltiple SIgnal Classification. The performance is also compared to the Cramér-Rao bounds of the wideband tensor model.