空间控制技术与应用2025，Vol.51Issue(4)：29-41,13.DOI:10.3969/j.issn.1674-1579.2025.04.003
基于HMM的空间非合作目标意图识别方法
Intention Recognition of Spatial Non-Cooperative Targets Based on HMM
摘要
Abstract
To address the challenge of recognizing the behavioral intentions of non-cooperative spacecraft targets in space,this paper proposes a dynamic time-series analysis method based on the hidden Markov model(HMM).This approach enables intention recognition without reliance on external prior knowledge(e.g.,target control models).The model learns the evolution patterns of typical target behaviors during the training phase and performs intention inference based on observation sequences during the testing phase.By comprehensively considering the characteristic features of typical non-cooperative behaviors,a behavioral sample dataset is constructed using the Monte Carlo shooting method.Three-dimensional observation sequences—comprising target distance,horizontal entry angle,and relative velocity—are defined,and a left-to-right HMM structure is designed to characterize the four-stage evolution of three types of intentions:hovering,rendezvous,and fly-around.Model parameters are learned via maximum likelihood estimation,and the forward algorithm calculates the log-likelihood of observation sequences to achieve accurate intention recognition.Numerical simulations validate the effectiveness of the proposed method.关键词
意图识别/非合作目标/隐马尔可夫模型/极大似然估计/态势评估Key words
intention recognition/non-cooperative target/hidden Markov model(HMM)/maximum likelihood estimation/situational assessment分类
航空航天引用本文复制引用
王维冬,丁一波,岳晓奎..基于HMM的空间非合作目标意图识别方法[J].空间控制技术与应用,2025,51(4):29-41,13.基金项目
国家自然科学基金资助项目(12372048)、中国博士后科学基金资助项目(2023M742835)、中国航天科技集团公司第八研究院产学研合作基金资助项目(SAST2024-001)、广东省基础与应用基础研究基金(2023A1515011421)、航空科学基金资助项目(2022Z004053001)和陕西省科学技术协会青年人才托举计划项目(20220509) National Natural Science Foundation of China(12372048),China Postdoctoral Science Foundation(2023M742835),Industry-Academia-Research Collaboration Fund of the Eighth Academy,China Aerospace Science and Technology Corporation(SAST2024-001),Guangdong Basic and Applied Basic Research Foundation(2023A1515011421),Aeronautical Science Foundation of China(2022Z004053001),and Young Talent Fund of Association for Science and Technology in Shaanxi(20220509) （12372048）
