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About

Andreas Sinn is a leading researcher in the emerging field of optical UAV detection and tracking, where he has pioneered the use of robotic telescope systems to address critical airspace security challenges. His work focuses on enabling long-distance, high-speed detection of small unmanned aerial vehicles through innovative combinations of deep learning, real-time image processing, and advanced control systems. Sinn’s most cited paper, “Feasibility Analysis of Optical UAV Detection Over Long Distances Using Robotic Telescopes” (22 citations), established the foundational viability of this approach. He further advanced the field with a parallel architecture for low-latency detection and tracking (12 citations) and a trajectory tracking control system for high-speed telescope positioning. His comparative study of color versus grayscale deep learning algorithms for long-distance detection has informed practical system design choices. With a total of over 40 citations across his published works, Sinn’s research directly addresses the growing safety concerns posed by versatile and accessible UAV technology, offering a scalable, optical solution for real-time threat detection and tracking in both laboratory and field environments.