Improving Power Spectral Density Estimation of Unmanned Aerial Vehicle Rotor Noise by Learning from Non-Acoustic Information
Benjamin Yen, Yusuke Hioka, Brian Richard Mace · 2018
A method to accurately estimate an unmanned aerial vehicle's (UAV) rotor noise power spectral density (PSD) is proposed, as part of the development of an effective UAV-mounted audio recording system that clearly captures the desired sound signals. Based on a previous study, the method seeks to improve rotor noise PSD estimation accuracy and robustness by utilising UAV rotor characteristics and microphone signals. Simulation results showed PSD estimation accuracy to within 1.3-3.3 dB log spectral distortion regardless of the presence of surrounding sound sources.