Reduced-Dimensional Polynomial Rooting-Based Multiple Parameter Estimation for Polarization Sensitive Coprime Arrays: A Full Array Extraction Perspective

Abstract

Generally, multi-dimensional spectral peak search (SPS) in parameter estimation for polarization sensitive coprime linear arrays (PS-CLAs) requires heavy computational burden. To resolve this problem, we propose a search-free algorithm for multi-parameter estimation with PS-CLAs in this paper. Specifically, different from the decomposition algorithms, we first reconstruct the total received signal of PS-CLA as the signal extracted from a large uniform linear array, which enables to offer a spectrum function only with regard to direction of arrival (DOA) by utilizing rank reduction estimator. Subsequently, we employ the polynomial root finding technique instead of one-dimensional SPS to directly calculate the DOA estimates. Furthermore, a quadratic optimization problem is established for the polarization parameters and in particular, the closed-form solutions are provided by utilizing Lagrange multiplier approach. Finally, numerical simulations illustrate that the proposed search-free algorithm can obtain improved estimation accuracy with remarkably low complexity.