空间控制技术与应用2025，Vol.51Issue(4)：42-51,10.DOI:10.3969/j.issn.1674-1579.2025.04.004
基于轨道知识图谱超边嵌入的卫星威胁事件预测方法
HyperKGE:Hyperedge-based Knowledge Graph Embedding for Satellite Threat Prediction
摘要
Abstract
In the increasingly complex aerospace environment,the growing number of satellites makes it critical to monitor and predict inter-satellite threat events such as conjunctions.Traditional methods rely on target recognition and tracking based on imagery and motion parameters,but these overlook the structural relationships between satellites and their orbits.In reality,such threat events often arise from higher-order interactions within the satellite-orbital network.To address this gap,we construct a satellite orbital knowledge graph centered on threat events.We model the complex semantics between satellites and their orbits through knowledge graph embedding techniques to predict potential threat events.We introduce a domain-driven hyperedge construction approach that captures high-order semantic relationships via metapaths,enabling integration of diverse information while maintaining semantic coherence.Additionally,we propose a soft contrastive learning mechanism that improves robustness and discrimination by enhancing the contrastive learning process in a complex semantic space.Experiments show that our method significantly outperforms existing approaches,offering a powerful new solution for satellite threat prediction and deeper insights into the structure of space object interactions.关键词
卫星威胁预测/轨道知识图谱/高阶语义关系/超边构建方法/软对比学习Key words
satellite threat events/orbital knowledge graph/hyperedge construction/high-order semantic relationships/soft contrastive learning分类
航空航天引用本文复制引用
李月华,黄琛,俞菲,孙畅..基于轨道知识图谱超边嵌入的卫星威胁事件预测方法[J].空间控制技术与应用,2025,51(4):42-51,10.基金项目
国家自然科学基金资助项目(U21B6001),辽宁省自然科学基金资助项目(025-MS-163) National Natural Science Foundation of China(U21B6001)and Liaoning Provincial Natural Science Foundation General Program(025-MS-163) （U21B6001）
