Long-Range Visual UAV Detection and Tracking System with Threat Level Assessment

Unmanned aerial vehicles (UAVs) can pose a serious threat to critical infrastructure which has motivated researchers to develop solutions for early detection. Nevertheless, the problem remains unsolved due to the limitations of the current detection techniques. In this paper, a vision-based approach using deep learning and a pan-tilt-zoom camera is proposed. In addition to detecting and tracking UAVs at long distances, the approach also assesses the threat level of the intruder UAVs based on their orientation. The proposed system offers long-range coverage while being cheap and practically feasible.