Acoustic Drone Detection for Technical Infrastructure Security and Defense Purposes

Abstract. With the widespread use of drones, new challenges have arisen in the field of technical security of facilitates and defense. This article discusses passive detection systems for unmanned aerial vehicles (UAVs) based on acoustic signatures. It presents an overview of methods for detecting drones using sound - from classical signal analysis and machine learning methods to modern deep learning algorithms - in the context of applications in critical infrastructure protection and military systems. Available solutions, their effectiveness and detection range were compared, and the difficulties of background noise and distinguishing between drone types were discussed. Research results were presented indicating high acoustic detection efficiency under favorable conditions (even above 90% using algorithms based on neural networks), as well as limitations caused by a decrease in signal-to-noise ratio with distance from the drone. The conclusion emphasizes the role of acoustic systems as a complement to other UAV detection techniques and their importance for maintaining safe operation of technical systems.