Researchers at Israel's Ben-Gurion University of the Negev (BGU) have learned to identify the location of a potentially malicious aerial drone operator operating near airports or other protected airspace by analyzing the drone's flight path.
Drone operators currently are pinpointed via radio-frequency techniques, using sensors around the flight area, which can then be triangulated; however, other wireless signals can mask drone signals.
The BGU team trained a deep neural network to predict the location of drone operators using only the flight path of the drones, making additional sensors unnecessary.
In tests with simulated drone routes, the model predicted operator locations with 78% accuracy.
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