A new security environment and the widespread availability of drones and other aircraft are creating threat scenarios for sensitive areas such as airports, military facilities, and large events. In order to respond appropriately, tools are needed to detect and locate potential sources of danger.
The Fraunhofer IDMT has developed a solution for the acoustic detection and localization of drones. This requires not only powerful microphones and audio signal processing technologies, but also machine learning methods. This allows audiological data to be used by acoustic sensors even in challenging environmental conditions, such as high ambient noise levels. Additional expertise in the discreet and effective enclosure and distribution of sensor technology expands the range of possible applications. The technology from Oldenburg works even without direct line of sight, which is particularly advantageous in forested and built-up areas.
Through objective, round-the-clock documentation of overflights, the Fraunhofer system supplements subjective sightings with verifiable data over a long period of time—regardless of visual conditions.
Every drone has an “acoustic fingerprint” that can be identified and stored in a database. Drone detection refers to the automated search for this fingerprint, i. e. a specific pattern in the acoustic signal that can be assigned to a drone.