空间控制技术与应用（中英文）2026，Vol.52Issue(2)：43-55,13.DOI:10.3969/j.issn.1674-1579.2026.02.005
基于孪生长短期记忆网络的角轨迹快速关联方法
A Fast Association Method for Angular Trajectories Based on Siamese Long Short Term Memory Network
摘要
Abstract
With the rapid growth in the number of space objects,the utilization of space-based optical systems for space object positioning holds significant importance for space security.As a critical component in multi-satellite collaborative positioning,angular trajectory association faces challenges with traditional geometry or kinematics-based methods,including combinatorial explosion,noise sensitivity,and poor real-time performance.This paper proposes a deep learning-based fast angular trajectory association method.By constructing multi-satellite multi-target simulation scenarios,simulated angular trajectory data are generated,and a Siamese long short-term memory network is designed for angular trajectory association.Experimental results demonstrate that,compared with traditional methods,the proposed method improves accuracy by about 3%and reduces inference time by more than 9 times.Therefore,this method can significantly increase the association speed of space multi-target trajectories while maintaining high accuracy,providing a reference for research on space objects'trajectory association.关键词
空间目标/孪生神经网络/长短期记忆网络/角轨迹关联Key words
space objects/siamese neural network/long short-term memory/angular trajectory association分类
航空航天引用本文复制引用
石晔轩,薛晓亮,杨帆,范达,史玮,张聪..基于孪生长短期记忆网络的角轨迹快速关联方法[J].空间控制技术与应用（中英文）,2026,52(2):43-55,13.基金项目
国家自然科学基金-航天联合基金重点项目(U23B2039) National Natural Science Foundation of China-Space Joint Fund Project(U23B2039) （U23B2039）
