Joint Estimation of Direction and Polarization for Partially Polarized Signals Using Tri-polarized Nested Array

Abstract

Using the dual-polarized array for underdetermined estimation of partially polarized (PP) signal parameters can lead to limited signal-to-ratio (SNR) and biased reconstruction of the coherency matrix. In this paper, a new non-iterative method is proposed with the tri-polarized nested array. With the sub-covariance addition, the power of different polarized components of a signal can be completely accumulated, which improves the SNR. Besides, it is proven that with the optimized tri-polarized nested array, noise variance estimation without iterations becomes possible in the underdetermined case, which is critical for unbiased coherency matrix reconstruction. The subspace-based method is adopted to estimate the direction-of-arrival (DOA), and the polarization parameters can be obtained based on the reconstructed coherency matrices. The proposed method is validated by numerical experiments and compared with other representative methods. It has relatively high accuracy and is about one order of magnitude faster than its competitor.