A multi-source perception driven unmanned aerial vehicle airborne acoustic collection noise reduction method and system

Abstract

This application discloses a multi-source sensing-driven airborne acoustic acquisition and noise reduction method and system for unmanned aerial vehicles (UAVs), belonging to the fields of array signal processing and airborne acoustic acquisition technology. This application acquires multiple sound signals through a MEMS acoustic array, performs STFT frequency domain decomposition, and integrates MEMS wind speed / turbulence, airframe vibration, and flight control motor speed / phase to construct wind noise and self-noise characteristic models, achieving active adaptive feedforward filtering. Combined with ICA blind source separation with flight control and vibration constraints, it decomposes rotor noise, wind noise, vibration interference, and target sound components. Then, it uses frequency-band dynamic weighted MVDR beamforming to suppress non-target direction noise and broadband interference, ultimately outputting a clean acoustic signal with high signal-to-noise ratio and low distortion. This application does not rely on sound source localization and focuses on improving sound acquisition quality under strong winds and strong self-noise conditions, and can be widely used in aerial photography, environmental monitoring, emergency sound acquisition, and other scenarios.

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