A team of researchers from Germany’s Fraunhofer Institute for Digital Media Technology (Fraunhofer IDMT) has developed a drone detection system that relies on acoustic signatures to identify and localize individual unmanned aerial vehicles (UAVs).

Current methods for detection include radar and cameras, but radar can be jammed while cameras rely on visual line of sight.

Source: Fraunhofer IDMT/Hannes Kalter

The new Fraunhofer system uses passive acoustic sensing and machine learning to detect and identify drones by their unique sound signatures, even in noisy environments. A network of microphones can also locate drones and determine their direction of travel. Because the technology can operate alongside radar, cameras and other sensors, it promises to offer another detection layer, specifically in urban or forested areas where drones may be hidden from view.

Importantly, due to the passive nature of acoustic sensors, the system does not actively transmit signals, which enables it to go undetected. Such technology could be used at airports, critical infrastructure, military facilities and large-scale events, for example.