Use of 5G and mmWave radar for positioning, sensing, and line-of-sight detection in airport areas

This paper explores innovative low-cost technologies, widely used outside of Air Traffic Management (ATM), for use in airport surface surveillance. These technologies consist of a 5G-signal-based surveillance solution and a millimeter wave (mmWave) radar augmented with artificial intelligence (AI). The 5G solution is based on the combination of 3D Vector Antenna, innovative signal processing techniques, and hybridization techniques based on time-of-arrival and angle-of-arrival estimates with uplink and downlink 5G signals, as well as Machine Learning (ML)-based Line of Sight (LOS) detection algorithms. The mmWave solution is based on mmWave radar for non-cooperative target’s positioning and sensing, combined with deep learning for objects classification. Standalone 5G positioning accuracy reaches m-level accuracy in LOS scenarios and it is better with downlink reference signals than with uplink ones, while it deteriorates quite drastically in NLOS scenarios. LOS detection accuracies above 84% average accuracy can be achieved with ML. The mmWave radar is tested in different scenarios (short, medium and long range) and it provides cost-effective surface surveillance up to few hundred meters (depending on the object radar cross section RCS) with ±60° field of view. The work is being conducted within the H2020 European-funded project NewSense and it delves into the 5G, Vector Antennas, mmWave, and ML/AI capabilities for future ATM solutions.