To address the key technical challenge of accurately separating and localizing noise sources from the propellers of quadrotor UAVs, this paper innovatively proposes an acoustic imaging method based on a 64-channel multi-arm logarithmic spiral array combined with the CLEAN-SC beamforming algorithm. The influence of array configuration on sound source identification performance was systematically investigated, and the results demonstrate that the multi-arm logarithmic spiral array with a diameter of 0.8 meters provides significant advantages in both dynamic range and angular resolution. Compared to traditional methods, this study achieves high-precision separation and imaging of the four propeller sound sources by leveraging the synergistic effect of an optimized array configuration and an advanced beamforming algorithm. Both simulations and experimental measurements in hovering scenarios validate the effectiveness of the proposed method, offering important insights for UAV noise control and structural optimization design.
Wang et al. (2026) studied this question.