空间控制技术与应用（中英文）2026，Vol.52Issue(4)：53-63,11.DOI:10.3969/j.issn.1674-1579.2026.04.006
面向空间防御的多航天器协同博弈方法
Multi-spacecraft Cooperation for Space Defense via Game Theory
摘要
Abstract
To address the cooperative observation and interception problem in multi-spacecraft space defense scenarios,this paper proposes a hierarchical intelligent cooperative architecture that integrates game theory and reinforcement learning.The architecture decouples observation task allocation and maneuver control:the upper-level observation game layer employs a Stackelberg game algorithm,which synthesizes solar angle constraints,observation distance,threat assessment,and information entropy for time-sensitive cooperative observation assignment.The lower-level control execution layer adopts the Multi-Agent Proximal Policy Optimization(MAPPO)algorithm,following a centralized training with decentralized execution paradigm,to realize autonomous interception control that complies with orbital dynamics and thrust constraints.To simulate the uncertain behaviors of non-cooperative spacecraft,a stochastic policy model is proposed based on the Clohessy-Wiltshire equations,by combining a deterministic baseline policy with Gaussian perturbations.Enabled by information sharing and fusion mechanisms,the system achieves a"one-point observation,global awareness"cooperative perception mode,significantly enhancing situational awareness.Simulation results demonstrate that the proposed hierarchical architecture effectively reduces computational complexity while improving system scalability and decision-making efficiency,and ensures high interception success rates with low fuel consumption.Thus,it provides a novel approach for multi-spacecraft cooperative missions in space confrontation scenarios.关键词
多航天器/空间防御/协同控制/Stackelberg博弈/MAPPO算法Key words
multi-spacecraft/space defense/cooperative control/Stackelberg game/MAPPO algorithm分类
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于常平,刘杨,曹志成,谢心如,张嘉辉..面向空间防御的多航天器协同博弈方法[J].空间控制技术与应用（中英文）,2026,52(4):53-63,11.基金项目
国家自然科学基金资助项目(62227810,62376015)和空间智能体系与基础研究中心开放基金资助项目(RCSISF-2025-11) National Natural Science Foundation of China(62227810,62376015)and Supported by the Open Foundation of Research Center for Space Intelligent Systems and Fundamentals(RCSISF-2025-11) （62227810,62376015）
