Abstract
A method to locate sound sources using an audio recording system mounted on an unmanned aerial vehicle (UAV) is proposed. The method introduces extension algorithms to apply on top of a baseline approach, which performs localisation by estimating the peak signal-to-noise ratio (SNR) response in the time-frequency and angular spectra with the time difference of arrival information. The proposed extensions include a noise reduction and a post-processing algorithm to address the challenges in a UAV setting. The noise reduction algorithm reduces influences of UAV rotor noise on localisation performance, by scaling the SNR response using power spectral density of the UAV rotor noise, estimated using a denoising autoencoder. For the source tracking problem, an angular spectral range restricted peak search and link post-processing algorithm is also proposed to filter out incorrect location estimates along the localisation path. Experimental results show the proposed extensions yielded improvements in locating the target sound source correctly, with a 0.0064–0.175 decrease in mean haversine distance error across various UAV operating scenarios. The proposed method also shows a reduction in unexpected location estimations, with a 0.0037–0.185 decrease in the 0.75 quartile haversine distance error.
Highlights
Unmanned aerial vehicles (UAVs) have recently gained huge popularity over a wide range of applications, such as filming [2], search and rescue [3], or security and surveillance [4]
This study proposes a rotor noise reduction algorithm based on accurate estimation of the rotor noise Power spectral density (PSD), which is incorporated into existing robust source localisation techniques
We present the details of the experimental setup of the given dataset, including the description of the UAV system, and various constraints found in the dataset
Summary
Unmanned aerial vehicles (UAVs) have recently gained huge popularity over a wide range of applications, such as filming [2], search and rescue [3], or security and surveillance [4]. Audio recording using UAVs has shown to be challenging due to the high noise levels radiated from the UAV rotors. This significantly affects the quality of the audio signals to aid with search and rescue, and with any applications [9,10,11,12]
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