Analysis on network properties of multivariate mixed air traffic management technical support system based on complex network theory
Authors: Wu Xi-Ping  , Yang Hong-Yu  , Han Song-Chen  ,   National Key Laboratory of Fundamental Science on Synthetic Vision, Sichuan University, Chengdu 610064, China
Published: December 2020

Air traffic management technical support system provides communication, navigation and surveillance service for air traffic management system and air traffic controller. The failures of some facilities may lead to large delay, even affect air transportation safety. In order to improve the ability of air traffic management technical support system to respond to emergencies, a network model of air traffic management technical support system is presented. The network model of air traffic management technical support system is established according to the effective coverage of communication, navigation and surveillance facilities, the position of air traffic management technical support system and air route network. Flexibility, robustness and efficiency are used to measure the network. The measure index of air traffic management technical support system network includes degree, degree distribution, strength, clustering coefficient, network performance, betweenness centrality, average shortest path and diameter. For Beijing, Shanghai, Guangzhou, Kunming, Shenyang and Lanzhou flight information regions, the air traffic management technical support networks are built by using the data of air traffic support facilities, air route, air traffic flow, etc. The average degrees, degree distributions, degree-degree correlations, clustering coefficients, average shortest paths and diameters of these netwoks are comparatively analyzed. The results show that the degrees of most nodes are between two and four. The network has a power law distribution, which is the same as that of air transportation network. The degree-degree correlation of air traffic management technical support system network is not assortative nor disassortative mixing, which has random network characteristics. The clustering coefficients of several air traffic management technical support system networks are between 0.25 and 0.39. The clustering value is lower than that of air transportation network. The shortest paths of air traffic management technical support system networks are between 3.16 and 5.05. The average shortest paths of these networks are all 3.4, which exhibits small world characteristics. Network attack based on degrees of priority and random is conducted to several flight information regions of air traffic management technical support network, showing the network is vulnerable. The network performance decreases quickly after degree priority attack. Some key nodes play an important role in the network. The network survivability can be improved after targeted immunized key nodes. The network performance can be improved by using more satellites based air traffic management technical support system. These rules provide theoretical support for improving and expanding air traffic management technical support system, and have practical significance for reducing the influence of emergency on air traffic management system support ability and ensuring the continuous safety of air traffic.