空军工程大学学报2025，Vol.26Issue(4)：40-47,8.DOI:10.3969/j.issn.2097-1915.2025.04.005
基于LSTM-DAE谱聚类的终端区飞行轨迹模式识别方法
A Method of Recognizing Flight Trajectory Pattern at Terminal Area Based on LSTM-DAE Spectral Clustering
摘要
Abstract
In order to solve the problems that dimensionality is high and feature extraction from flight tra-jectory data is inaccurate at the terminal area,this paper proposes a trajectory pattern recognition method based on LSTM-DAE spectral clustering.Firstly,the paper plans to achieve dimensionality reduction and to extract feature from the processed trajectory dataset by the LSTM-DAE network,and then proceed to even more accurately capture the nonlinear features of trajectory.Secondly,spectral clustering is employed by using the extracted trajectory features to complete pattern partitioning.Finally,an example analysis is conducted on the entry flight trajectory data at Tianjin Binhai Airport.The experiment shows that this method can accurately cluster high-dimensional flight trajectories after extraction,and can be divided into six categories of trajectory clusters,achieving still higher clustering quality.And the method can provide support for effectively identifying flight trajectory pattern features at the terminal area.关键词
飞行轨迹/轨迹聚类/LSTM/深度自编码Key words
flight trajectory/trajectory clustering/LSTM/deep auto-encoder分类
航空航天引用本文复制引用
张召悦,许程..基于LSTM-DAE谱聚类的终端区飞行轨迹模式识别方法[J].空军工程大学学报,2025,26(4):40-47,8.基金项目
国家重点研发计划项目(KJZ25420200012) （KJZ25420200012）
中央高校基本科研项目(3122022105) （3122022105）
