计算机应用与软件2024，Vol.41Issue(7)：67-73,7.DOI:10.3969/j.issn.1000-386x.2024.07.011
基于生成对抗网络的三维空间民航轨迹预测模型
3D FLIGHT TRAJECTORY PREDICTION MODEL BASED ON GENERATIVE ADVERSARIAL NETWORK
摘要
Abstract
Flight trajectory data has the problems of uneven sampling time and inconsistent spatial dimension.Moreover,the existing trajectory prediction methods are mainly oriented to ground traffic trajectory such as pedestrians and vehicles,and there are few flight trajectory prediction methods applicable to three-dimensional space.To address the above problems,this paper proposes a prediction model for 3D flight trajectory based on generative adversarial network.The model resampled the flight trajectory data to unify the sampling time interval and eliminate the influence of extreme variation between different spatial dimension.The time series characteristics in the data and the interaction information between different targets were used to generate the predicted trajectory.Experiments show that compared with traditional trajectory prediction methods,the proposed model reduces the ADE by more than 29％,which verifies the effectiveness of the model in the prediction of flight trajectory in 3D space.关键词
轨迹预测/民航轨迹/长短时记忆网络/生成对抗网络Key words
Trajectory prediction/Flight trajectory/LSTM/Generative adversarial network分类
信息技术与安全科学引用本文复制引用
曹建制,佟强,陈玉立,刘秀磊..基于生成对抗网络的三维空间民航轨迹预测模型[J].计算机应用与软件,2024,41(7):67-73,7.基金项目
国家重点研发计划项目(2017YFB1400402,2018YFC0830202) （2017YFB1400402,2018YFC0830202）
网络文化与数字传播北京市重点实验室开放课题项目(ICDDXN006) （ICDDXN006）
北京信息科技大学勤信人才项目(2020) （2020）
面向边缘计算的创新科研平台建设项目(2020KYNH105). （2020KYNH105）
