Trajectory clustering for arrival aircraft via new trajectory representation  

作　　者：GUI Xuhao ZHANG Junfeng PENG Zihan 

机构地区：[1]College of Civil Aviation,Nanjing University of Aeronautics and Astronautics,Nanjing 211106,China

出　　处：《Journal of Systems Engineering and Electronics》2021年第2期473-486,共14页系统工程与电子技术（英文版）

基　　金：supported by the Joint Fund of National Natural Science Foundation of China and Civil Aviation Administration of China(U1933117);the Open Fund for Graduate Innovation Base(Laboratory)of Nanjing University of Aeronautics and Astronautics(kfjj20190709).

摘　　要：Trajectory clustering can identify the flight patterns of the air traffic,which in turn contributes to the airspace planning,air traffic flow management,and flight time estimation.This paper presents a semantic-based trajectory clustering method for arrival aircraft via new proposed trajectory representation.The proposed method consists of four significant steps:representing the trajectories,grouping the trajectories based on the new representation,measuring the similarities between different trajectories through dynamic time warping(DTW)in each group,and clustering the trajectories based on k-means and densitybased spatial clustering of applications with noise(DBSCAN).We take the inbound trajectories toward Shanghai Pudong International Airport(ZSPD)to carry out the case studies.The corresponding results indicate that the proposed method could not only distinguish the particular flight patterns,but also improve the performance of flight time estimation.

关 键 词：air traffic management trajectory clustering trajectory representation flight pattern 

分 类 号：V355.1[航空宇航科学与技术—人机与环境工程] TP311.13[自动化与计算机技术—计算机软件与理论]