Systematic Detection of Drones at Airports

Since August of this year, the German air navigation service provider DFS has been conducting drone tests at Frankfurt and Munich, Germany’s two busiest airports. The objective is to determine whether and how reliably state-of-the-art detection systems can actually identify drones.

The issue of drones operating in controlled airspace and interfering with air traffic has developed into a major problem, especially when they operate without authorisation in the vicinity of airports. Since 2015, DFS has recorded over 500 drone-related interferences at Germany’s 16 international airports. Nearly 360 of them have occurred in the last two years, causing serious disruptions to air traffic and preventing air traffic controllers from allowing aircraft to take-off or land due to safety concerns. This resulted in both flight cancellations and delays, which in turn had severe economic consequences. In early 2020, for example, Germany’s busiest airport in Frankfurt was forced to shut down for a total of 4.5 hours due to drones being spotted in the airport’s immediate vicinity. According to estimates of Euro control, the European Organisation for the Safety of Air Navigation, each flight cancellation incurs average costs of €17,650, while each delayed flight incurs approximately €6,600 per hour.

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. Uncooperative drones do not make themselves visible or identifiable and pose a major threat to both manned and unmanned air traffic at and around airports.

DFS believes that unmanned aviation has great benefits. When used in rescue services, for example, drones can save lives. However, nobody benefits from flights being cancelled or delayed due to drones being spotted around airports. In 2019, the German Ministry of Transport, therefore, commissioned DFS with systematic drone detection at the country’s 16 international airports. One of the requirements defined was for drones to be detected at up to 10 nautical miles from runways as a way of preventing any risk of interference with aircraft taking off or on their final approach. 

However, the specific capabilities of the drone detection technologies currently available are not yet clear. As such, DFS was also initially commissioned to determine what is actually possible in terms of detecting drones in environments as challenging as major international airports.

Pushing drone detection systems to their limits

Over the past four months, DFS has been working with its partners Fraport AG and Flughafen München GmbH, the operator of Munich Airport, on a test project with a level of 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 10 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 systems

When 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 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 drone"

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.