Anti-Mainlobe-Interference Adaptive Beamforming for Unmanned Aerial Vehicles Communication

Abstract

In UAV communication, the high mobility of UAVs causes frequent mainlobe switching, which may turn sidelobe interference into mainlobe interference under which conventional adaptive beamforming (ABF) suffers severe performance degradation. To address this issue, this paper investigates an interference-plus-noise covariance matrix (INCM) reconstruction ABF using a polarization-sensitive array (PSA) under mainlobe interference conditions. Specifically, the objective is to suppress interference from both the mainlobe and sidelobes as accurately as possible while exerting virtually no effect on the desired signal. First, we employ the MUSIC algorithm to estimate the direction of arrival (DOA), polarization phase angle, and polarization phase difference with the PSA. Subsequently, the DOA and polarization parameters of the interference are identified to reconstruct the INCM for beamforming. Simulation results demonstrate that the proposed algorithm outperforms the INCM-based beamforming using a conventional uniform linear array.