Detection and Localization of Drones and UAVs Using Sound and Vision
Erik Tegler, Max Modig, Per Skarin, Kalle Åström, Magnus Oskarsson, Gabrielle Flood · 2025
In this paper, we present a system for drone detection and positioning. The approach uses a system composed of an audio detection rig with a set of microphones, a set of fixed cameras with a large combined field of view and a Pan-TiltZoom camera. We present how this system can be defined in an efficient and modular way with a number of parallel sensing modules. The focus of this work is the audio detection and positioning system. We show that we can use direction-of-arrival methods to efficiently position a drone from its ambient emitted sound only, up to several hundred meters distance. The audio system is tested in a real setting, using several different drones, in a number of real flight experiments, with promising results. The dataset with the real audio recordings is available online11https://vision.maths.lth.se/drone_sound/. Future work includes how to combine the audio processing with the vision system.