Preprint
Securing the Skies: A Comprehensive Survey on Anti-UAV Methods, Benchmarking, and Future Directions
16 Apr 2025
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 highlighting open research directions, we aim to foster innovation and guide
the development of next-generation defense strategies in an era marked by the
extensive use of UAVs.
Metrics
39 Record Views
Details
- Title
- Securing the Skies: A Comprehensive Survey on Anti-UAV Methods, Benchmarking, and Future Directions
- Creators
- Yifei DongFengyi WuSanjian ZhangGuangyu ChenYuzhi HuMasumi YanoJingdong SunSiyu HuangFeng Liu - Drexel University, Computer ScienceQi DaiZhi-Qi Cheng
- Resource Type
- Preprint
- Language
- English
- Academic Unit
- Computer Science
- Other Identifier
- 991022048715504721