5G AeroMACS-Based Object Detection Method for Airport Scenarios

In recent years, the pressure of airport surface surveillance has gradually increased with the rapid development of civil aviation transportation industry. Existing surface surveillance technology suffers from blind spots. Currently, new surveil-lance technologies are constantly emerging. Some can reduce surveillance blind spots, but they also require a large number of receiving stations. When used in large airports, they face difficulties in equipment support and data transmission. To address the blind spots of existing surveillance systems without introducing new equipment, this paper proposes a communication-sensing integrated target detection method based on 5G Aeronautical Mobile Airport Communications System (5G AeroMACS). The method utilizes the aviation dedicated frequency band 5091-5150MHz for communication while enabling the base station to sense surface targets (aircraft, vehicles, and people) by receiving reflected echoes. In target detection, neural network methods are used to improve target detection performance. In addition, the terrain within the sensing range is considered as the basis for the authenticity of the target. The simulation results show that the target sensing and detection method based on 5G AeroMACS can realize the authenticity judgment and information acquisition of the target within the coverage range of the base station. The proposed method effectively assists airport surface surveillance.