[2504.11967] Securing the Skies: A Comprehensive Survey on Anti-UAV Methods, Benchmarking, and Future Directions

Computer Science > Computer Vision and Pattern Recognition arXiv:2504.11967 (cs) [Submitted on 16 Apr 2025 (v1), last revised 29 Mar 2026 (this version, v4)] Title:Securing the Skies: A Comprehensive Survey on Anti-UAV Methods, Benchmarking, and Future Directions Authors:Yifei Dong, Fengyi Wu, Sanjian Zhang, Guangyu Chen, Yuzhi Hu, Masumi Yano, Jingdong Sun, Siyu Huang, Feng Liu, Qi Dai, Zhi-Qi Cheng View a PDF of the paper titled Securing the Skies: A Comprehensive Survey on Anti-UAV Methods, Benchmarking, and Future Directions, by Yifei Dong and 10 other authors View PDF Abstract:Unmanned Aerial Vehicles (UAVs) are indispensable for infrastructure inspection, surveillance, and related tasks, yet they also introduce critical security challenges. This survey provides a wide-ranging examination of the anti-UAV domain, centering on three core objectives-classification, detection, and tracking-while detailing emerging methodologies such as diffusion-based data synthesis, multi-modal fusion, vision-language modeling, self-supervised learning, and reinforcement learning. We systematically evaluate state-of-the-art solutions across both single-modality and multi-sensor pipelines (spanning RGB, infrared, audio, radar, and RF) and discuss large-scale as well as adversarially oriented benchmarks. Our analysis reveals persistent gaps in real-time performance, stealth detection, and swarm-based scenarios, underscoring pressing needs for robust, adaptive anti-UAV systems. By highlight...