Contribution
Acoular Workshop: Generating Synthetic Sound Pressure Time Datasets of Multicopter Drone Fly-bys
* Presenting author
Abstract:
The investigation of noise generated by multicopter drones and its environmental impact is a growing field of research.Two major challenges include identifying optimal measurement setups for comprehensive drone noise characterization and predicting noise exposure at specific locations based on varied operational parameters.Direct measurements are often impractical due to the complexity of testing different sensor arrangements and the required number of measurements.A simulation-based approach, on the other hand, is more efficient in that regard and allows for flexible variations of the involved parameters.This contribution explores the open-source software package Acoular and its ability to simulate sound pressure data as if it were captured by an array of spatially distributed microphones.In a step-by-step walkthrough, key aspects regarding the acoustics of a drone fly-by are illustrated via their implementations in Acoular. This includes simulating typical drone signals in the time domain, directional emission patterns, movement of the drone, sound propagation under varying atmospheric conditions (e.g. with and without wind), and ground reflections.The resulting datasets provide a robust basis for testing measurement setups, allow the mapping of noise metrics based on time signals, and can also be used for auralization purposes.