高师理科学刊2024，Vol.44Issue(3)：43-50,8.DOI:10.3969/j.issn.1007-9831.2024.03.007
机场附近频繁变换场景下的6D飞行轨迹预测
6D flight trajectory prediction in scenarios with frequent scene changes near the airport
摘要
Abstract
The increasing volume of aviation activities poses challenges to air traffic control,with trajectory prediction technology playing a pivotal role in ensuring the safety and orderliness of airspace traffic.The heightened density of flights near airports presents difficulties for trajectory prediction.A hybrid neural network model based on Attention-CNNs,bidirectional long short-term memory(LSTM),and XGBoost is proposed using data from the automatic dependent surveillance-broadcast(ADS-B)system.This model is designed to forecast 6D information pertaining to flight trajectories,including time,longitude,latitude,altitude,velocity,and heading angle.A trajectory dataset composed of spatial-temporal information and flight dynamics data is used to validate the efficiency of our approach.Quantitative analysis reveals that the proposed model outperforms comparative models in terms of evaluation metrics.This method offers an effective solution for ensuring the safe operation of aviation management systems in airport environments.关键词
航空交通管理/轨迹预测/卷积神经网络/双向长短时记忆网络/注意力机制Key words
air traffic management/trajectory prediction/CNN/bidirectional long short-term memory(BiLSTM)/attention mechanism分类
信息技术与安全科学引用本文复制引用
陈昂,李敬有,李大辉..机场附近频繁变换场景下的6D飞行轨迹预测[J].高师理科学刊,2024,44(3):43-50,8.基金项目
齐齐哈尔大学研究生创新项目(YJSCX2022013) （YJSCX2022013）
黑龙江省规划办项目(GJB1421345) （GJB1421345）
齐齐哈尔大学教育科学研究项目(GJZRYB202030) （GJZRYB202030）
