The advances in antenna technology, high-frequency technology, semiconductor technology, algorithms and integrated circuits will in future enable the performance of radar systems and new applications to be improved. Research topics in the competence sector are concerned with adaptive, cognitive, multi-static, multifunctional and networked radar systems, but also intelligent countermeasures to reduce disruptive effects. As modern radar systems are becoming more agile and intelligent, the counterpart, in other words, electronic intelligence systems, is also required to adapt its techniques. For this purpose, basic principles are being developed through experiments. In addition, advances in the recognition, tracking and identification of drones is being assessed, for example, to detect drones in built-up areas.

In future, it will be possible to detect well camouflaged positions with hyper-spectral sensors from long distances. Hyper-spectral sensors measure the material properties, which enables, for example, a green camouflage net to be distinguished from green vegetation in good weather conditions. In contrast, imaging radar sensors (Synthetic Aperture Radar SAR) are managing to send high-resolution reconnaissance images of the earth, even in overcast conditions – at any time of the day or night and even from great distances. The further development of SAR technology promises to detect human activity on the ground in real time and to identify the smallest changes. SAR devices are installed on drones and manned aircraft. SAR systems on satellites are becoming increasingly important due to miniaturisation and new business models.

The significance of intelligent, sensor-based evaluation will increase sharply over the coming years. On the one hand, data quantities are increasing due to the advances in the semiconductor technologies of detectors. These large volumes of data need to be evaluated and reduced locally. On the other hand, the further development of artificial intelligence and integrated circuits enables technological solutions for sensor-based integration of modern algorithms. The advances towards local intelligence, in other words, edge and tiny-edge technology, should therefore be pursued and evaluated. Furthermore, heterogeneous sensors are being used increasingly on a networked basis. The data and information fusion of this type of sensor is increasing in significance and new technological solutions are required, particularly for modern C2 (Command and Control) systems. In this competence area, the trends and limits of intelligent and networked surveillance are therefore being identified and assessed.

The new developments in detector and sensor technology are being evaluated with respect to their performance limits. This relates to multi-sensor systems, miniaturisation and sensor systems that access new spectral bands, as well as new methods of wide-angle reconnaissance. Research is also being carried out into new approaches for increasing sensor distances and for deployments in urban terrain (e.g. through-wall sensing).

Knowledge of the signatures of targets and background is an essential requirement for assessing modern camouflage and target detection. Signature analysis is therefore considered using simulations and measurements in the radar range, in the visual and infra-red spectrum as well as in the acoustic range. Furthermore, the advances made in multi-spectral, mobile and adaptive camouflage are being collected and evaluated. This also applies to new options in material technology. What is of additional interest is camouflage and deception compared with modern artificial intelligence in reconnaissance. Furthermore, new options for shot and shooter detection in challenging situations, such as with warning sensors on helicopters or in urban areas will be demonstrated in this competence area.

The technology demonstrator MIRANDA-35 enables airborne images to be taken of the ground even in weather conditions under which other sensors would not be able to deliver usable information (such as clouds or rain). Quick-look images, i.e. low-resolution remote sensing images generated on the aircraft immediately after measurement recording can be transmitted by radio to a ground station. The measurement data stored on the aircraft can be converted into images with a high pixel resolution of 10 cm after a mission. The technology demonstrator comprises five receiving channels, with which moving targets on the ground and in the air, polarimetric properties of ground targets, the smallest changes as well as the height information of the terrain and large objects can be determined.

Due to engine noise, helicopter crews are unlikely to hear gunshots aimed at their aircraft. It is therefore even more important in such cases for pilots to receive automatic warnings indicating the proximity of hazardous zones. In order to develop expertise in this area, a Cougar helicopter has been fitted with 14 special microphones for test purposes.

The desired reconnaissance result can often not be achieved with a single sensor. The multi-sensor platform makes it possible to exploit the potential of sensor data fusion.

The technology demonstrator comprises a hexacopter, a power and data cable for the drone as well as a ground station. The cable has a length of 100 metres, although operations typically take place 80 metres above ground. The weight of the cable comprises 1.6 kilograms for 100 metres length – in other words, 16 grams per metre of cable length. The data can be transmitted at a data rate of 40 megabits per second. The drone automatically controls the rotors, so that it can fly steadily on the spot. In addition, an emergency parachute is integrated for safety reasons. Currently, a gimbal system with visual and infra-red camera is integrated on the drone as payload. The use of an overall system for reconnaissance and surveillance purposes could, for example, be demonstrated to the troops for drone detection or surveillance tasks. Automatic detection and tracking of air and ground targets will be considered in a future step. 

The UDPD (Urban Drone Presence Detection) technology demonstrator consists of several distributed microphone devices and one central evaluation unit. The microphone devices are operated by battery and are independent of wind conditions. They measure the noise in their environment and send the audio data to a central unit for visualisation and monitoring. This procedure enables the central unit to show the noise situation in real time. Furthermore, the central unit automatically determines whether a drone is located near the microphone device for each device. The distance from the drone to the microphone device is also estimated. Some basic data of a microphone unit:

• Signal spectrum: 10 Hz to 8 kHz
• Signal level: 25 – 130 dB
• Time synchronisation accuracy: <1 microsecond
• Data rate of wireless communication: 256 kbps
• Power: 0.8 W
• Runtime: 8 hours, it is possible to connect a solar panel

Four programmable software-defined radio radar devices are controlled by a central unit. The time synchronisation is based on the GPS signals. The following research topics are examined using the demonstrator:

• Non-linear radar waveforms
• Radar networks, in other words, fusion of radar detection from several radar devices
• Cognitive radar algorithms
• Noise radar technology, i.e. methods for camouflaging radar devices
• RADCOM topics, i.e. basic principles on the co-existence of radar and communication
• Multi-static radar approach
• Drone detection in urban terrain

A single radar node has the following characteristics:

Antennas: One transmitting and two receiving antennas

Operating modes: Frequency-modulated continuous wave procedure and freely programmable waveforms

Radar frequency: 8.2 – 10.6 GHz

Bandwidth: 160 MHz for the continuous wave procedure and 80 MHz for freely programmable waveforms

Output rating: 2 W, or 20 W

Traditional radar devices work in a mono-static case, which means that only one antenna is used or the transmitting and receiving antennas are at the same location. If transmitting and receiving antenna are now set up separately with regard to location, a gain in diversity can be expected, for example with respect to the reception performance of the radar waves backscattered from the target or in terms of Doppler velocity. A second, additional receiver can increase diversity even more. The technology demonstrator has the following basic values:

• Frequency band: C band, 5.2 – 5.8 GHz
• Bandwidth: Maximum 50 MHz
• Number of antennas: 1 transmitting and 2 receiving antennas
• Transmitting antenna: Phased array
• The maximum peak output is 400 W
• The electronic swivel range is 90°
• Receiving antenna consists of eight WiFi antennas each, which electronically control eight receive directions
• Search area: 5 km x 5 km

The acoustic camera with 120 microphones enables the detection and localisation of several noise sources in real time, such as the detection and localisation or tracking of drone noise. The azimuth and elevation directions of the noise sources measured with the acoustic camera can be used for aligning additional sensors (such as camera on a swivel-tilt platform). Altogether, the acoustic camera can monitor the immediate surroundings acoustically on six freely selectable target frequencies with individual frequency bands at the same time.