DOA Estimation Algorithm for Reconfigurable Intelligent Surface Co-Prime Linear Array Based on Multiple Signal Classification Approach

Abstract

Co-prime linear arrays (CLAs) provide an additional degree of freedom (DOF) with a limited number of physical sensors, and thus help to improve the resolution of direction of arrival (DOA) estimation algorithms. However, the DOF of traditional CLA is restrained by the structure of the array, which cannot be adjusted after deployment. In this paper, we propose a DOA estimation algorithm for reconfigurable intelligent surface co-prime linear array (RIS CLA) based on the multiple signal classification approach. Specifically, an RIS CLA is first constructed on the ground of RIS antenna, by turning on/off specific elements at different times. Then, the covariance matrix of the received signal is vectorized, so as to construct a virtual difference array, whose aperture is considerably expanded. Finally, a spectral peak search on the noise subspace of the received signal of the difference array is conducted to obtain the DOA estimation result. Simulations verify the improvement of the proposed algorithm in terms of DOF and resolution. To be specific, the DOF provided by RIS CLA outnumbers that of CLA by more than 30%, and the resolution of the proposed DOA estimation algorithm is effectively improved, with its accuracy increased up to 70% under the low signal-noise-ratio (SNR) scenario, compared with existing algorithms.