Abstract:
In many wireless scenarios, e.g., wireless communications, radars, remote sensing, direction-of-arrival (DOA) is of great significance. In this paper, by making use of electromagnetic vector sensors (EVS) array, we settle the issue of two-dimensional (2D) DOA, and propose a covariance tensor-based estimator. First of all, a fourth-order covariance tensor is used to formulate the array covariance measurement. Then an enhanced signal subspace is obtained by utilizing the higher-order singular value decomposition (HOSVD). Afterwards, by exploiting the rotation invariant property of the uniform array, we can acquire the elevation angles. Subsequently, we can take advantage of vector cross-product technique to estimate the azimuth angles. Finally, the polarization parameters estimation can be easily completed via least squares, which may make contributions to identifying polarization state of the weak signal. Our tensor covariance algorithm can be adapted to spatially colored noise scenes, suggesting that it is more flexible than the most advanced algorithms. Numerical experiments can prove the superiority and effectiveness of the proposed approach.
