Despite great potential for improving public safety, use of drones can also lead to very undesirable situations, such as privacy, safety violations or property damage. Radar technology is one of the solutions to monitor the presence of drones and prevent possible threats. Due to their varying sizes, shapes and composite materials, drones can be challenging to detect.
Researchers from Aalto University (Finland), UCLouvain (Belgium) and New York University (USA) have gathered extensive radar measurement data, aiming to improve the detection and identification of drones. Researchers measured various commercially available and custom-built drone models, Radar Cross Section (RCS), which indicates how the target reflects radio signals. The RCS signature can help to identify the size, shape and the material of the drone.
The publicly accessible measurement data can be utilised in the development of radar systems, as well as machine learning algorithms for more complex identification. This would increase the probability of detecting drones and reducing fault detections.
Researchers suggest that 5G base stations could be made in the future for surveillance.