V-USDT: Vision-Based UAV Swarm Detection and Tracking by Leveraging Swarm Formation Constraints

The rapid proliferation of Unmanned Aerial Vehicles (UAVs) and UAV swarm technologies has raised critical concerns about security and safety in low-altitude airspace. In response, we propose a vision-based system for detecting and tracking UAV swarms, which combines a novel UAV detection mechanism with a swarm tracking strategy. Our UAV detector incorporates parallel receptive field blocks alongside an attention mechanism to enhance detection performance. This design effectively captures multiscale features of UAVs while prioritizing salient features, ensuring robust detection under diverse conditions. For swarm tracking, we leverage the inherent formation constraints typically maintained by UAV swarms. These constraints allow us to improve tracking accuracy, particularly in scenarios involving occluded UAVs or those with weak appearance features. By integrating the enhanced UAV detector with the formation-aware swarm tracking framework, our approach achieves notable advancements in both detection and tracking performance.