Empirical study of airport geofencing for unmanned aircraft operation based on flight track distribution

Abstract

With the increasing activities of unmanned aircraft (UA) near airports, severe challenges have emerged regarding airport safety management. This paper presents a brand-new data-driven based approach to accurately design the geofencing for UAs around an airport, focusing on midair collision risk between commercial flights and small UAs which is considered as the most important hazard. In premise, prevalent trajectory extraction from real flight tracks is realized based on an advanced and general model, taking the advantage of describing turning legs which is more popular in terminal area. As a key solution, a Gauss-Laplace-composite distribution is provided for rigorous estimation of flight track distribution in line with the extracted prevalent trajectory. Based on those, airport geofencing is proposed consisting of an inner critical area and an outer buffer area. This approach can be adaptive for different traffic patterns of an airport. The buffer area is an extension range to help the execution of some defense measures. Results of an empirical study for setting up geofencing for small UAs around Chongqing Jiangbei International Airport (ZUCK) show the superiority of the proposed approach, which indicates that it can provide practical application, especially varying from different target level of safety.