Duke researcher uses self-teaching computers to identify drones

Drone detection in dense city centers poses major challenges – when it’s not flat-out impossible. But one Duke University researcher thinks he may be on the way to solving that problem by pairing old-school radar technology up with self-teaching computers.

IDing potential drone security threats to cities

Radar is pretty good at identifying airborne planes and distinguishing those from, say, hang gliders. Ditto friendly jets from hostile aircraft. By contrast, it starts to struggle when beamed down into crowded city streets. It does okay with cars and buses, but throw joggers, skateboarders, or bikes moving with irregular trajectories and speeds into the mix, and things get confusing. 

Drones, meantime, can come off looking like stationary objects or the spinning blades of air conditioning fans amid that visual stew. In failing to stand out, they sort of become invisible to surveillance technologies. And that would pose a security problem should someone decide to use a…