42 Focus | Swarming of the calculations can be performed onboard, such as instructions to fly relative to a neighbouring UAV. Once it has received that message it knows what it has to do with high-level commands from the ground and the system can manage itself. There is also the issue of dealing with third-party aircraft in the airspace around the swarm. These can be collaborative aircraft that have ‘no fly’ zones defined around them so that the members of the swarm fly relative to them; for example, with a crewed aircraft whose position is fed into the vehicle-to-vehicle network and shared with all the UAVs in the swarm. For non-collaborative aircraft, the methodology depends on the environment in which the swarm is operating and the sensors the UAVs have, such as cameras. The data from these sensors needs to be fed into the MCC, where it can be shared between the UAVs in the swarm and connect to other GCSs. The communications link is vital. UAVs could be hundreds of kilometres apart in a swarm and linked by satellites, with several aircraft providing surveillance data and linked back to uncrewed fast jets that can cover a distance of 50 to 60 km in a few minutes. The key is to know the rate for each type of information. With a swarm the ground operator is no longer a pilot but a mission coordinator, managing 20, 30 or 40 aircraft. The key is to increase the amount of data that can be stored in the UAV and not transmitted to the ground all the time. There also needs to be a way of preventing duplicated data, such as the same data from different UAVs, being transmitted multiple times. For a heterogenous swarm, such as uncrewed surface vessels (USVs) at sea, the coordination of the swarm is managed by linking the GCSs. Using a swarm can also improve the resilience of a mission. A mesh network with connections between the UAVs in the swarm allows for any errors in a sensor on one aircraft to be shared with the others, with algorithms using this error data to improve the navigation of the other craft. There is an advantage in the payloads, which can be distributed between multiple UAVs rather than requiring a larger aircraft. For example, four small, 25 kg UAVs flying together can each carry a payload, rather than one large, 100 kg craft. This can provide more data from different points of view, such as triangulation to find a radio source. Using smaller aircraft of less than 25 kg has less regulatory requirements than larger ones. This has been tested in trials of UAVs with a takeoff weight of over 100 kg flying in autonomous formation. They achieved speeds of over 300 kts with separations of less than 200 m. Another trial in the UK saw four fixedwing Albatross UAVs teamed to carry out a mission to detect and jam a radio frequency emitting from an enemy target. Each UAV was equipped with a mission system, and it used multispectral machine vision and new search algorithms to respond to its environment, and to the other UAVs in the swarm. This builds on a series of autonomous flight trials that took place last year using an adaptable autonomy software framework to build intelligent behaviours deployable on multiple platforms. The second-phase trials now include swarming, or autonomous platformto-platform teaming, which can target a position from a greater range and lets the platforms cover more ground with confidence in target identity and location. February/March 2025 | Uncrewed Systems Technology Connecting a swarm with linked ground-control systems (Image courtesy of UAV Navigation) A swarm of four Boeing Albatross UAVs is on trial in the UK (Image courtesy of Applied Aeronautics)
RkJQdWJsaXNoZXIy MjI2Mzk4