2D-DOA for a Monostatic ULA EMVS-MIMO Radar Based on RC-ESPRIT

Abstract

Electromagnetic vector sensor (EMVS) embedded multiple-input multiple-output (MIMO) radar is an emerging technology that enables two-dimensional (2D) direction of arrival (DOA) estimation. In this paper, we proposed a low-complexity estimation of signal parameters via rotational invariance techniques (ESPRIT) algorithm for uniform linear array (ULA) EMVS-MIMO radar at a monostatic, enabling rapid estimation of 2D target angles. Initially, by employing a selection matrix, complexity reduction is applied to the array data, thereby eliminating redundancy in the array data. Subsequently, leveraging the rotation invariance propagator method (PM) algorithm, obtain the estimation of the elevation angle, but due to array sparsity, this estimation exhibits ambiguity. Then, the vector cross-product (VCP) technique is employed to achieve unambiguous 2D-DOA estimation. Finally, the aforementioned estimates are synthesized to obtain high-resolution, unambiguous elevation angle estimation. The proposed algorithm is applicable to large-scale and spare EMVS-MIMO radar systems and provides higher estimation accuracy compared to existing ESPRIT algorithms. The effectiveness of the algorithm is verified through matrix laboratory (MATLAB) simulations.

Keywords

electromagnetic vector sensors / sparse array / DOA estimation / reduced complexity / propagator method