Estimating Power Spectral Density of Unmanned Aerial Vehicle Rotor Noise Using Multisensory Information
Benjamin Yen, Yusuke Hioka, Brian Richard Mace · 2018
A method to accurately estimate the power spectral density (PSD) of an unmanned aerial vehicle (UAV) is proposed, in anticipation of being used for a UAV-mounted audio recording system that clearly captures target sound while suppressing rotor noise. The method utilises UAV rotor characteristics as well as microphone recorded signals to combat practical limitations seen in a previous study. The proposed method was evaluated on a simulation platform modelled after the UAV used in the previous study. Results showed that the proposed method was able to estimate the rotor noise PSD to within 1.3-3.3 dB log spectral distortion (LSD) regardless of the presence of surrounding sound sources.