Airport: Software predicts drone attacks
A new system from researchers at the University of Cambridge can largely rule out false alarms.
Researchers of the University of Cambridge have developed a new method for countering drone attacks on airports. This combines data from radar surveillance of the airspace with statistical calculation methods. The result is an almost certain prediction of the drone's flight path. This could prevent a repeat of an incident like the one at London's Gatwick Airport in 2018. Back then, hundreds of flights were canceled because of fears that a drone could endanger takeoffs.
Target of the drone predictable
The researchers' new technology can identify drones that are trying to enter the airspace above an airport based on their flight paths. At the same time, it excludes flying objects that do not pose a threat. The software-based solution uses a stochastic or random model to identify the drone's target early on, even though it could change at any time. Simon Godsill's team takes advantage of a peculiarity of drone navigation. They navigate with intermediate targets that they head for in a straight line, in a sense shimmying from waymark to waymark.
The program analyzes the flight path of a drone, its speed and characteristics such as flight altitude. From this, it determines in real time the waymark that the drone will head for next, even before it reaches it. After several analyses, the program recognizes the final target and sounds an alarm if it is in danger, so that flight operations can be stopped or the drone destroyed. False alarms are said to be eliminated. In tests in the environment of virtual airports, the drone targets could be predicted with a high hit rate. Threats were detected within seconds, he said. In a real scenario, it is crucial for security whether a threat is detected in seconds or minutes.
