Detection, classification, tracking, and defense against small drones (cUAS)

Task force brings together drone defense expertise

The threat posed by drones is growing, both in the civilian and military sectors, and with it the pressure to take action, for example on the part of operators of critical infrastructure. Fraunhofer IOSB possesses a wide range of expertise required for the detection and classification of drones, as well as for the operational management of threat situations and, where necessary, the deployment of countermeasures, ranging from optronic sensors to powerful analysis and tracking methods, situational awareness and decision-support systems, and high-energy lasers, particularly those operating at wavelengths around 2 µm, which offer various advantages for counter-drone applications.

The Drone Defense Task Force, serving as the central hub, brings together these competences from Fraunhofer IOSB in the field of cUAS (counter-UAS, UAS = unmanned aerial systems). It identifies requirements across a broad range of operational scenarios, aligns development efforts, and supports the creation of demonstration and reference systems.

Roadmap

Our strategic goal is to maintain a state-of-the-art system platform and further develop key capabilities in line with our scientific strengths. This applies in particular to:

• the detection and classification of drones using optronic sensors (cameras operating in the visible and infrared spectrum),
• robust tracking and video documentation, as well as, in the next development phase, the demonstration of countermeasures using high-energy lasers operating at wavelengths optimized for eye-safe operation,
• the use of specialized sensors such as high-speed and event-triggered cameras, gated-viewing systems, or laser Doppler vibrometers, as well as other modalities such as RF scanners, acoustics, radar, or lidar, depending on operational requirements, to improve detection reliability, range, and classification accuracy.

Previous work

Our work is based on the MODEAS (modular drone detection and assistance system) research and demonstration system. MODEAS uses radar for early warning and combines it with optical sensors and laser rangefinding for precise tracking. The video analysis algorithms reliably detect and identify drones even against complex backgrounds such as vegetation or urban structures. MODEAS is based on cost-effective sensors and can be expanded modularly. This opens up the prospect of significantly lower system costs compared to many solutions currently available on the market.

A video recording and documentation system for unauthorized drone overflights has already been implemented.