Feasibility Analysis of Optical UAV Detection Over Long Distances Using Robotic Telescopes

Abstract

In recent years, substantial technological development has made unmanned aerial vehicles (UAVs) more versatile, cheaper, and accessible to the public. Alongside many positive effects and use cases, safety concerns are increasing as a plethora of incidents demonstrate the destructive potential of UAVs. To counteract this development and, thus, protect people and critical infrastructure, UAV detection, tracking, and defense has gained more and more research attention. Whereas different drone detection technologies such as RADAR, radio frequency, and acoustic detection are deployed within multispectral systems, optical detection and imaging of approaching objects provide key information to correctly assess the situation. As reaction time is a crucial parameter for successful UAV defense, the operating distance of the optical detection system needs to be improved further. This article presents the analysis, development, and evaluation of a telescope-based UAV detection system. The system consists of a high-precision mount and a telescope equipped with a camera. UAVs are detected in the captured video frames by the deep learning algorithm YOLOv4 using a modified architecture. The proposed system, which uses an $f$/10 telescope with a focal length of $f$ = 2540 mm and a camera equipped with a 7.3 mm × 4.1 mm sensor, allows a significant increase in the optical detection range to more than 3 km of UAVs down to 0.3 m in diameter under daylight conditions and sufficient contrast, extending the reaction time significantly for counter UAV systems.