空军工程大学学报2026，Vol.27Issue(2)：1-7,7.DOI:10.3969/j.issn.2097-1915.2026.02.001
基于LightGBM算法的飞行冲突探测研究
A Flight Conflict Detection Method of Integrating Spatial Geometric Modeling and Machine Learning Based on LightGBM Algorithm
摘要
Abstract
Aimed at the problems that timeliness is poor in geometric flight conflict detection methods and detec-tion samples are imbalanced in machine learning-based detection methods,this paper proposes a flight conflict de-tection method of integrating spatial geometric modeling and machine learning.Firstly,in combination of synthetic multi-dimensional features such as aircraft position and velocity,the geometric method is used to determine con-flicts based on the velocity obstacle method and the three-dimensional cylindrical protection zone.In order to ad-dress the poor timeliness of geometric judgment,a machine learning method is introduced.Conflict samples being short and training samples being imbalanced,the lightweight Gradient Boosting Machine(LightGBM)algorithm with a class weight adjustment mechanism is selected.Finally,the proposed method is verified by using actual sec-ondary radar data collected in the Xi'an area.The experimental results show that the operating speed by the pro-posed method is 3.91 times faster than that by the geometric method.Compared with typical algorithms such as Random Forest(RF)and K-Nearest Neighbors(KNN),the proposed method in conflict judgment is an accuracy increase of 19％and 91％respectively.关键词
冲突探测/航空器保护区/LightGBM算法/不均衡数据Key words
conflict detection/aircraft protection zone/LightGBM algorithm/imbalanced data分类
航空航天引用本文复制引用
张立彪,温祥西,吴明功,梁亮,李佳威,彭川,苏蕊..基于LightGBM算法的飞行冲突探测研究[J].空军工程大学学报,2026,27(2):1-7,7.基金项目
国家自然科学基金(71801221) （71801221）
国家社会科学基金(22XGL001) （22XGL001）
