Multi-sensory sound source enhancement for unmanned aerial vehicle recordings

Abstract

A method to effectively perform sound source enhancement from an unmanned aerial vehicle (UAV)-mounted audio recording system is proposed. The objective of this study is to utilise audio recordings and non-acoustical UAV rotor characteristics to improve rotor noise power spectral density (PSD) estimation accuracy and robustness. The improved rotor noise PSD estimate in turn improves the effectiveness of the rotor noise postfilter, leading to improvement in source enhancement performance. The performance of the proposed source enhancement algorithm is evaluated via experiments, with recordings made in an outdoor environment with an in-flight UAV. Experiment results show PSD estimation accuracy to within 1.5 dB log spectral distortion regardless of the given input conditions, such as the presence of surrounding sound sources. The method also achieves a consistent ∼20–25 dB improvement in source enhancement performance, where the effects of rotor noise from the noisy microphone recordings are significantly reduced. The proposed method also outperforms existing state-of-the-art such as the beamformer with postfilter and speech distortion weighted multichannel Wiener filter frameworks.