With the increasing number of geosynchronous orbit satellites with expiring lifetime,spacecraft refueling is crucial in enhancing the economic benefits of on-orbit services.The existing studies tend to be based on pre...With the increasing number of geosynchronous orbit satellites with expiring lifetime,spacecraft refueling is crucial in enhancing the economic benefits of on-orbit services.The existing studies tend to be based on predetermined refueling duration;however,the precise mission scheduling solution will be difficult to apply due to uncertain refueling duration caused by orbital transfer deviations and stochastic actuator faults during actual on-orbit service.Therefore,this paper proposes a robust mission scheduling strategy for geosynchronous orbit spacecraft on-orbit refueling missions with uncertain refueling duration.Firstly,a robust mission scheduling model is constructed by introducing the budget uncertainty set to describe the uncertain refueling duration.Secondly,a hybrid harris hawks optimization algorithm is designed to explore the optimal mission allocation and refueling sequences,which combines cubic chaotic mapping to initialize the population,and the crossover in the genetic algorithm is introduced to enhance global convergence.Finally,the typical simulation examples are constructed with real-mission scenarios in three aspects to analyze:performance comparisons with various algorithms;robustness analyses via comparisons of different on-orbit refueling durations;investigations into the impacts of different initial population strategies on algorithm performance,demonstrating the proposed mission scheduling framework's robustness and effectiveness by comparing it with the exact mission scheduling.展开更多
This paper proposes a threat assessment framework for non-cooperative satellites by analyzing their motion characteristics,developing a quantitative evaluation methodology,and demonstrating its effectiveness via repre...This paper proposes a threat assessment framework for non-cooperative satellites by analyzing their motion characteristics,developing a quantitative evaluation methodology,and demonstrating its effectiveness via representative scenarios with neural network acceleration.The framework first establishes a threat evaluation model that integrates three core parameters:capability,opportunity,and hidden values.Subsequently,this research systematically investigates the critical role of transfer windows in threat quantification and introduces a transfer window-based threat assessment approach.The proposed methodology is validated through multiple representative scenarios,with simulation results demonstrating superior performance compared to conventional methods relying solely on optimal transfer windows or minimum distance metrics,enabling more nuanced threat ranking in scenarios where traditional techniques prove inadequate.To address computational demands,a neural networkbased approximation system is implemented to achieve a 25,200×speedup(0.005 s vs.baseline 126 s per 1000-sample batch)through parallel processing,maintaining 99.3%accuracy.Finally,the study explores the framework's extensibility to diverse NCS objectives.It identifies discrepancies between intention inference models and threat evaluation paradigms,providing methodological insights for next-generation space domain awareness systems.展开更多
以测量空间非合作目标旋转特性为背景,对比传统光度法,提出了基于匹配项绝对差值之和(sum of absolute differences of matches,SDM)匹配算法的高光谱特征反演方法.首先,以高光谱成像原理为基础,对各种旋转角度的卫星模型进行投影,使用...以测量空间非合作目标旋转特性为背景,对比传统光度法,提出了基于匹配项绝对差值之和(sum of absolute differences of matches,SDM)匹配算法的高光谱特征反演方法.首先,以高光谱成像原理为基础,对各种旋转角度的卫星模型进行投影,使用光谱成像仪测量卫星目标轨迹,得到了呈现周期性变化规律的光谱特征.然后,对不同旋转角度下卫星模型的光谱曲线进行光谱特征差异计算,分析目标旋转过程中的光谱相似角曲线.最后,建立仿真模型,得到空间目标的旋转周期和旋转角速度.结果表明:高光谱特征反演法可用于测量空间非合作慢旋失稳目标的旋转特性,相较于传统光度法精度提高了0.05,显著提升了对空间非合作目标旋转特性的测量能力.展开更多
基金co-supported by the National Natural Science Foundation of China(Nos.62473110,62403166)the Fundamental Research Funds for the Central Universities,China(No.2023FRFK02043)+1 种基金the Natural Science Foundation of Heilongjiang Province,China(No.LH2022F023)the National Key Laboratory of Space Intelligent Control Foundation,China(No.2023-JCJQ-LB-006-19)。
文摘With the increasing number of geosynchronous orbit satellites with expiring lifetime,spacecraft refueling is crucial in enhancing the economic benefits of on-orbit services.The existing studies tend to be based on predetermined refueling duration;however,the precise mission scheduling solution will be difficult to apply due to uncertain refueling duration caused by orbital transfer deviations and stochastic actuator faults during actual on-orbit service.Therefore,this paper proposes a robust mission scheduling strategy for geosynchronous orbit spacecraft on-orbit refueling missions with uncertain refueling duration.Firstly,a robust mission scheduling model is constructed by introducing the budget uncertainty set to describe the uncertain refueling duration.Secondly,a hybrid harris hawks optimization algorithm is designed to explore the optimal mission allocation and refueling sequences,which combines cubic chaotic mapping to initialize the population,and the crossover in the genetic algorithm is introduced to enhance global convergence.Finally,the typical simulation examples are constructed with real-mission scenarios in three aspects to analyze:performance comparisons with various algorithms;robustness analyses via comparisons of different on-orbit refueling durations;investigations into the impacts of different initial population strategies on algorithm performance,demonstrating the proposed mission scheduling framework's robustness and effectiveness by comparing it with the exact mission scheduling.
基金supported by the National Key R&D Programof China:Gravitational Wave Detection Project(Grant Nos.2021YFC2026,2021YFC2202601,2021YFC2202603)the Na-tional Natural Science Foundation of China(Grant Nos.12172288and 12472046)。
文摘This paper proposes a threat assessment framework for non-cooperative satellites by analyzing their motion characteristics,developing a quantitative evaluation methodology,and demonstrating its effectiveness via representative scenarios with neural network acceleration.The framework first establishes a threat evaluation model that integrates three core parameters:capability,opportunity,and hidden values.Subsequently,this research systematically investigates the critical role of transfer windows in threat quantification and introduces a transfer window-based threat assessment approach.The proposed methodology is validated through multiple representative scenarios,with simulation results demonstrating superior performance compared to conventional methods relying solely on optimal transfer windows or minimum distance metrics,enabling more nuanced threat ranking in scenarios where traditional techniques prove inadequate.To address computational demands,a neural networkbased approximation system is implemented to achieve a 25,200×speedup(0.005 s vs.baseline 126 s per 1000-sample batch)through parallel processing,maintaining 99.3%accuracy.Finally,the study explores the framework's extensibility to diverse NCS objectives.It identifies discrepancies between intention inference models and threat evaluation paradigms,providing methodological insights for next-generation space domain awareness systems.
文摘以测量空间非合作目标旋转特性为背景,对比传统光度法,提出了基于匹配项绝对差值之和(sum of absolute differences of matches,SDM)匹配算法的高光谱特征反演方法.首先,以高光谱成像原理为基础,对各种旋转角度的卫星模型进行投影,使用光谱成像仪测量卫星目标轨迹,得到了呈现周期性变化规律的光谱特征.然后,对不同旋转角度下卫星模型的光谱曲线进行光谱特征差异计算,分析目标旋转过程中的光谱相似角曲线.最后,建立仿真模型,得到空间目标的旋转周期和旋转角速度.结果表明:高光谱特征反演法可用于测量空间非合作慢旋失稳目标的旋转特性,相较于传统光度法精度提高了0.05,显著提升了对空间非合作目标旋转特性的测量能力.
