Digital sensor network to monitor air traffic at vertiports

Researchers at the Fraunhofer Institute for High Frequency Physics and Radar Techniques FHR have been developing an entirely digital sensor network, including a radar sensor, that in the future will be able to closely monitor air traffic at so-called ‘vertiports’ (landing sites for drones and air taxis) and ensure safe flight operations. Not only is the system being considered for use in vertiports, it could also monitor corridors across cities used by transportation drones.

At the 2024 Olympic Games in Paris, the first passengers in Europe will be transported by air taxis, with air travel companies planning to equip Olympic venues with electrical vertical take-off and landing systems (eVTOLs) to transport visitors to events directly from the airport. Initially, these drone systems will be piloted by a human, with one passenger per taxi; in the coming years, they could be piloted autonomously. An important aspect of this concept is the safety of the vertiports used for launching and landing eVTOLs, which will be integrated into roofs, train stations, parking lots and other urban structures.

Researchers at Fraunhofer FHR aimed to tackle an important part of the safety of the new drone stops by equipping them with a modular, fully digital sensor network including a radar sensor. The network can be adapted to the size of each vertiport and uses both active and passive sensors with fully autonomous functionality, linking to each other and collectively sensing the port.

“The nodes are fully digital, and each sensor in the network functions entirely autonomously,” explained Oliver Biallawons, a scientist at Fraunhofer FHR. “The sensors aren’t coordinated by a central computer unit; they network themselves. They are able to independently localise and organise themselves. Based on the principle of edge computing, each sensor has its own computer unit and can detect the location of other sensors in the network.”

The job of sending and receiving is shared between the individual sensors, which coordinate with each other. The decentralised active and passive sensors are installed on the ground and work together to sense the entire take-off and landing pad as well as the airspace above it. The network decides which sensor to operate in active (sending and receiving) and passive (receiving only) mode as required. The more sensors in the network, the greater the area that can be monitored. Even if a sensor or radar node is added or removed, the radar network can continue to function flawlessly.

The key to the network’s autonomous organisation and decentralised processing is the connection between the individual nodes via wireless communication channels integrated into the radar signal. By integrating the network communication in the radar signal, the signal can be seamlessly integrated into future telecommunications infrastructures. This represents an important milestone on the path toward merging fully fledged radar and telecommunications, according to Biallawons.

“We are integrating the communication signal into the radar waves instead of using separate channels for radar and communication,” he said.

Another key feature of the so-called Civil Drone Systems (CDS) Network is that, in contrast to test monitoring systems based on mobile radio, the system is able to detect eVTOLs that don’t have a communication device such as a chip or tag. With the addition of AI, the safety solution can not only detect obstacles that block incoming or outgoing flight paths but also classify them. This means that it is able to classify objects such as trees, birds and drones. The radar network can even recognise the size of a drone and how many rotors it has.

“As urbanisation continues to progress, we expect at some point to see transport systems take to the air, too,” Biallawons said. “This can only be achieved with the help of sophisticated safety systems, such as our modular, resilient network of low-radiation, communicating radar nodes, which can achieve flawless take-off and landing.”

Image ©Fraunhofer FHR/Andreas Schoeps