The white paper titled Cloud Detection System for UAV Sense and Avoid: Cloud Distance Estimation using Triangulation , by Adrian Dudek and Peter Stütz from University of Bundeswehr Munich, was awarded Best of Session at the 39th Digital Avionics Systems Conference (DASC) in October, 2020. This research relied on Presagis tools such as Vega Prime and FlightSIM.
Sense and Avoid is gaining importance in the integration of unmanned aerial vehicles (UAVs) into civil airspace. In order to be seen by other air traffic participants operating under visual flight rules (VFR), own visibility must be granted. This includes the observance of legal minimum cloud distances. An airborne electro-optical cloud detection and avoidance system could cope with this task on unmanned platforms. In this paper we propose an approach for cloud distance estimation using computer vision algorithms. In addition to the functional architecture, results from a simulation environment are shown and the demands for future developments are addressed.