DOA Estimation Based on Antenna Current Green's Function Using Compressive Sensing

This paper introduces CS-ACGF, a new approach that integrates compressive sensing with the antenna current Green's function to enhance resolution and reduce required number of samples for direction of arrival estimation. Previous methodologies addressing DOA issues often overlook the mutual coupling effects in antenna arrays, leading to inherent limitations in angle estimation resolution. Building on the established MUSIC-ACGF methodology, which effectively models received voltage signals in the presence of strong mutual coupling effects, this study aims to reduce demands for required number of signal samples while improving resolution in DOA estimation. To achieve this, the proposed method employs compressive sensing, specifically h-regularized least-squares method, to optimize processing time without compromising the resolution and accuracy of DOA estimation. For validation, a uniform linear array of seven half-wavelength dipole antennas operating at 2.4 GHz is used as the receiving antenna, with various incident wave environments serving as the transmitting sources. The proposed CS-ACGF method demonstrates high resolution in DOA estimation compared to conventional methods.