A Comprehensive Review of Modern Counter-Drone Technologies: Trends, Challenges, and Future Directions

Abstract

The rapid proliferation of unmanned aerial vehicles (UAVs)/ drones, has brought about significant advancements in various fields such as military operations, surveillance, agriculture, and logistics. However, the misuse of drones poses substantial risks to security, privacy, and safety. This comprehensive review explores the current state of counter-drone technologies, examining trends, challenges, and future directions. We delve into various detection, tracking, and mitigation techniques, including radar, radio frequency (RF) sensing, computer vision, and artificial intelligence (AI)-driven approaches. Furthermore, the paper highlights the integration of deep reinforcement learning (DRL) in enhancing the efficacy of counterdrone systems. Key issues such as legal and ethical considerations, technological limitations, and emerging threats have been discussed in detail. The review synthesizes findings from recent literature, offering a detailed analysis of the capabilities and constraints of existing counter-drone technologies. This work aims to provide a foundation for future research and development in creating robust, efficient, and adaptable counter-drone systems to mitigate the evolving threats posed by rogue drones.