December, 20219 detail that has never before been seen. This involves testing drone detection systems from six different technology providers at the airports of Frankfurt and Munich for drones operating both on and within ten nautical miles of airport grounds. DFS chose Munich and Frankfurt for the testing, as each airport has a different layout, different types and distribution of buildings, as well as different green areas. Following a comprehensive market survey of European suppliers, technology providers were selected using a transparent assessment model.A range of drone types was then operated day and night. The drones used, which comprised both standard and customised models, ranging from small and agile multi-rotor systems to larger drones with higher payload, as well as more substantial fixed-wing systems that can reach speeds of up to 90 mph. Challenging flight manoeuvres were carried out, such as rapid ascents to 1,000 feet above ground level, rapid changes of direction and swarm flights, in which drones followed different flight paths.The challenge presented by airports for drone detection systemsWhen detecting drones at airports, the key challenge is that detection systems often struggle to differentiate between actual targets and other objects which are not drones. These include moving objects in the vicinity of airports, such as cars, birds, or helicopters. Reliably identifying drones among other moving elements is a critical and vital requirement of any detection system. After all, false alarms increase the workload for the detection system operator and serve to hinder efficient drone defence activities by law enforcement. To identify drones effectively, the systems are equipped with a variety of sensors. The most important are the primary radars, radio frequency detectors, and video cameras. Combining the sensors offering the best performance with the most suitable technology in terms of the respective airport's size, layout, and operational concept is generally the most promising approach to securing effective drone identification. All data provided by the system then need to be analysed by an intelligent multi-sensor data fusion engine in order to provide the correct position and corresponding track for each single object. In addition, the detection system should be able to interact with air traffic management systems for both manned and unmanned aviation. Tower air traffic controllers, for example, would then access data via their controller working position in order to be able to react to possible interference. The findings from this test project will not only be of fundamental importance for the German Ministry of Transport, which will in turn provide DFS with specific requirements to establish systematic drone detection at airports, but also be very valuable for the future development of drone detection technologies. TO SECURE THE SAFE INTEGRATION OF UNMANNED AIRCRAFT SYSTEMS IN THE AIRSPACE, IT IS ESSENTIAL TO IDENTIFY NOT ONLY AUTHORISED DRONES, BUT ALSO SO-CALLED UNCOOPERATIVE DRONES
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