The application of unmanned aerial vehicles (UAVs) has gained considerable momentum in recent years, with a marked reduction in costs, attracting growing interest from diverse fields. Nevertheless, as their prevalence continues to rise, amateur UAVs operating recklessly at low altitudes have become a serious threat to public safety. As a result, an economically efficient preventive solution is urgently required to identify potential UAV-related threats at an early stage. Acoustic-based detection offers a cost-effective and easily deployable solution on a large scale while also addressing certain limitations of other technologies (such as radar, radio frequency, and visual systems), thus holding considerable research significance. In this work, we review the research developments in acoustic-based UAV detection, highlighting the involved key technologies of UAV acoustic signals, such as signal acquisition, blind source separation, feature extraction and recognition, and sound source localization. A wide range of technical methods and application strategies employed in existing research are thoroughly covered, with an organized analysis of the relevant technological framework, detailing its core principles and representative methods, and comparing their merits and limitations in addressing UAV detection tasks. In addition, the challenges and problems faced by acoustic-based UAV detection are examined, with a discussion of the development paths required to fulfill its anticipated future potential.
Kang et al. (Mon,) studied this question.