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Metrics for Assessing the Perception of Drone Noise

Abstract : Unmanned Aerial Vehicle (UAV) technology is rapidly advancing, and therefore, the potential for UAV use seems almost unlimited at this stage. Diverse UAV stakeholders are currently exploring the feasibility of different UAV applications for monitoring, intervention to improve or support public services and parcel delivery. It seems quite likely that, in a short while, communities in urban areas will be inundated with a new source of noise due to UAV operations that they had not before encountered. Noise has been suggested as one of the major barriers of UAVs to public acceptance, and therefore, for the expansion of the sector. The noise of UAVs does not resemble the noise of contemporary aircraft (or any other transportation noise), which leads to an important uncertainty in the prediction of the resultant perception of UAV noise. Previous research has suggested that contemporary noise metrics are unable to account for the qualitative aspects of the particular features of UAV noise. Based on a previous psychoacoustic characterisation of a small fixed-pitch quadcopter, this paper presents the results of a listening experiment as a first approach for the development of metrics optimised for UAV noise. Preliminary results suggest that a combined metric including tonality and loudness-sharpness interaction is able to account for the perceptual features of UAV noise.
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https://hal.archives-ouvertes.fr/hal-03233630
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Submitted on : Wednesday, May 26, 2021 - 1:00:55 PM
Last modification on : Thursday, June 3, 2021 - 10:37:07 AM
Long-term archiving on: : Friday, August 27, 2021 - 7:27:34 PM

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Antonio J Torija Martinez, Zhengguang Li. Metrics for Assessing the Perception of Drone Noise. Forum Acusticum, Dec 2020, Lyon, France. pp.3163-3168, ⟨10.48465/fa.2020.0018⟩. ⟨hal-03233630⟩

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