Virtual Array Interpolation for 2-D DOA and Polarization Estimation Using Coprime EMVS Array via Tensor Nuclear Norm Minimization

In this article, we develop an interpolation-based algorithm for two-dimensional (2-D) direction-of-arrival (DOA) and polarization estimation with coprime electromagnetic vector-sensor (EMVS) array. First of all, we derive the tensor form coarray output of coprime EMVS array, and perform virtual array interpolation on the output components of the difference coarray. Subsequently, we construct a low-rank third-order augmented tensor using the interpolated uniform linear array output, and derive two important properties for this low-rank tensor in the Fourier domain. Based on these properties, we reconstruct a noise-free third-order augmented tensor by formulating a tensor nuclear norm (TNN) minimization problem. Finally, we derive the closed-form expressions of 2-D DOA and polarization estimates using the reconstructed tensor. Unlike the existing techniques, our approach not only avoids losses in array aperture and degrees-of-freedom, but also exploits the multidimensional structure inherent in the coarray output. Numerical results demonstrate the superiority of the proposed algorithm over the existing approaches.