A Drone Net under development by Embry-Riddle Aeronautical University could provide a cost-effective way to protect small airports from irresponsible unmanned aerial vehicle (UAV) operators.
The technology, based on a network of passive rooftop sensors that capture electro-optical and infrared (EO/IR) data, continuously scans the sky. If Drone Net detects a UAV without a flight plan or off its flight plan, the system will cue an EO/IR camera to slew and track the target until it leaves the area.
Drone Net uses a machine-based learning system designed to automatically classify aerial objects. The researchers believe the machine-learning approach could perform as well as, or perhaps better, than radar.
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