LAUSR

With the development of aviation, the air traffic density in the terminal area is high and the traffic situation is relatively complex, which brings challenges to the flight deployment. In order to fully understand the air flight situation and provide decision-making basis for controllers, this paper proposes a key conflict aircraft identification method based on complex network theory and node deletion method. First, an aircraft state network is constructed with an aircraft as nodes and airborne collision avoidance system (ACAS) communication relations as edges. Network efficiency, network robustness, connection density, and largest component were used as the indexes of network performance. The weight of each index is determined by using AHP-entropy weight method. A multi-attribute decision-making method was introduced to quantify network performance. Then we used a node deletion method to determine key conflict aircrafts. The simulation and experiment are respectively carried out on the artificial network and the aircraft state network of a certain day in the terminal area of Kunming Changshui Airport. The results show that the method proposed in this paper can identify the key conflict points in the aircraft state network. The deployment of selected nodes can not only effectively reduce the complexity of the flight state network, but also provide a reference for air traffic control services and reduce the control difficulty of the controller.