On-Board Outdoor Acoustic Measurement of Multirotor Unmanned Air Vehicles: Effect of Flight Conditions on Emission and Perception

Urban Air Mobility development depends on overcoming several challenges. Noise emission is one of the most critical, making Unmanned Air Vehicles’ acoustic characterisation a scientific and regulatory priority. Through an on-board outdoor measurement campaign on three commercial multirotor drones (DJI Mavic 3M, Mavic 3 Classic, and DJI Matrice 4T) during hovering, this study analyses and shows the effects that the most important flight variables: altitude, propeller design and payload, have on the overall noise emission, its directivity and the psychoacoustic annoyance, more specifically through the descriptor developed by Boucher. The results showed that different altitudes (10, 15 and 20 m) do not affect noise emissions. Moreover, overall sound pressure levels may fail to discriminate drones’ noise annoyance. In fact, despite the lower sound pressure levels, for the specific platform and propeller configuration tested (DJI Mavic 3M with manufacturer low-noise blades), the low-noise-propeller configuration showed higher psychoacoustic annoyance than the standard-propeller one, driven primarily by higher roughness (and, to a lesser extent, tonality). Additional payloads (50–150 g) did not increase psychoacoustic annoyance monotonically. The heaviest Matrice 4T showed the most stable psychoacoustic profile, with psychoacoustic annoyance remaining below its unloaded baseline at all payload levels, while the lightest Mavic 3 Classic showed the largest swing. Moreover, considering the drone’s structural symmetry, the angular asymmetries revealed by the directivity analysis suggest hovering-stabilisation dynamics attributions. Overall sound pressure levels alone proved an unreliable predictor of drones’ noise annoyance across all tested flight conditions.

Authors

Institutions

Publication Details

Journal
Applied Sciences
Published
2026-09-25
DOI
https://doi.org/10.3390/app16199527
Primary Topic
Aerodynamics and Acoustics in Jet Flows
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
article

On-Board Outdoor Acoustic Measurement of Multirotor Unmanned Air Vehicles: Effect of Flight Conditions on Emission and Perception

Luigi Maffei, Massimiliano Masullo, Juan M. Navarro, Nicola GRAVINA
Applied Sciences
Aerodynamics and Acoustics in Jet Flows
article

On-Board Outdoor Acoustic Measurement of Multirotor Unmanned Air Vehicles: Effect of Flight Conditions on Emission and Perception

Luigi Maffei, Massimiliano Masullo, Juan M. Navarro, Nicola GRAVINA
article en

Abstract

Urban Air Mobility development depends on overcoming several challenges. Noise emission is one of the most critical, making Unmanned Air Vehicles’ acoustic characterisation a scientific and regulatory priority. Through an on-board outdoor measurement campaign on three commercial multirotor drones (DJI Mavic 3M, Mavic 3 Classic, and DJI Matrice 4T) during hovering, this study analyses and shows the effects that the most important flight variables: altitude, propeller design and payload, have on the overall noise emission, its directivity and the psychoacoustic annoyance, more specifically through the descriptor developed by Boucher. The results showed that different altitudes (10, 15 and 20 m) do not affect noise emissions. Moreover, overall sound pressure levels may fail to discriminate drones’ noise annoyance. In fact, despite the lower sound pressure levels, for the specific platform and propeller configuration tested (DJI Mavic 3M with manufacturer low-noise blades), the low-noise-propeller configuration showed higher psychoacoustic annoyance than the standard-propeller one, driven primarily by higher roughness (and, to a lesser extent, tonality). Additional payloads (50–150 g) did not increase psychoacoustic annoyance monotonically. The heaviest Matrice 4T showed the most stable psychoacoustic profile, with psychoacoustic annoyance remaining below its unloaded baseline at all payload levels, while the lightest Mavic 3 Classic showed the largest swing. Moreover, considering the drone’s structural symmetry, the angular asymmetries revealed by the directivity analysis suggest hovering-stabilisation dynamics attributions. Overall sound pressure levels alone proved an unreliable predictor of drones’ noise annoyance across all tested flight conditions.

Applied SciencesVol. 16(19)
University of Campania "Luigi Vanvitelli" (IT), Universidad Católica de Murcia (ES)
Sustainable cities and communities
Openalex Percentile: Top 8%
Aerodynamics and Acoustics in Jet Flows
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.