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摘要: 如何利用有限的星上资源执行复杂繁重的空间任务长期以来备受关注，随着卫星载荷能力不断提升，响应时间要求不断缩短，卫星自主与协同任务调度规划研究的重要性逐渐增大.本文从单星任务调度规划为起点，对单星地面离线任务调度规划、单星星上在线任务调度规划、单星星地一体化自主任务调度规划研究现状进行梳理与分析，然后延展至多星领域，综述了多星地面离线协同任务调度规划、多星星上在线协同任务调度规划、多星星地一体协同任务调度规划研究现状.最后，对卫星自主与协同任务调度规划研究进行了总结与展望.Abstract: How to make use of limited resources on a satellite for complex and heavy space tasks has attracted much attention. With the continuous improvement on satellite load capacity and reduction of response time requirements, the importance of satellite autonomous and collaborative task scheduling research has gradually increased. This paper starts with the research status of single-satellite task schedule planning. From single-satellite ground off-line task schedule planning and online task schedule planning, this paper analyzes the research on single-satellite integrated autonomous task schedule planning, then extends up to the present situation of satellite task schedule planning research including multiple-satellite ground offline collaborative task schedule plan and satellite onboard collaborative task schedule plan. Finally, the research on satellite autonomous and collaborative task scheduling is prospected.1) 本文责任编委 倪茂林
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表 1 卫星地面离线任务调度规划算法
Table 1 Single-satellite offline task scheduling algorithms
算法类型 算法名称 应用场景/算法特性 精确算法 动态规划[28] 基于合成任务间时序特征, 将问题按照卫星的最大侧摆次数划分为多个阶段, 利用动态规划思想, 得到了问题的最优解. 分支定价[29] 用期望模型和机会约束规划模型对卫星调度问题进行数学建模, 将分支定界与列生成混合起来求解该问题. 贪婪算法[30] 在卫星可见时间窗和任务时间窗的约束条件下, 满足最大化资源利用的目标. 禁忌搜索[31] 针对操作约束下的对地观测卫星任务选取与调度问题, 使用禁忌搜索寻找近似最优方案. 拉格朗日松弛和线性搜索[32] 将对地观测卫星的日常成像调度问题建模成整数规划问题, 结合拉格朗日松弛法和线性搜索法来求解此问题. 遗传算法[33] 结合电磁探测卫星的具体约束条件, 建立了观测任务和数据传输的坐标调度模型, 使用遗传算法求解. 近似算法 粒子群算法[34] 在粒子群算法中使用局部领域拓扑结构来避免过早收敛, 并引入分支定界法来提高局部搜索能力. 差分进化[35-36] 为实现突变和交叉对进化个体进行实数编码, 用贪婪规则选择每代较优个体, 解码获得资源分配方案与任务执行时间序列. 蚁群算法[37] 应用均匀设计确定蚁群算法的组件, 设计出了高效求解敏捷卫星调度问题的蚁群算法. 蜂群算法[38] 采用人工蜂群算法对中继卫星调度问题进行求解, 对比发现蜂群算法优于其他群智能算法. 模拟退火[3] 设计模拟退火诸多机制:自适应温度控制、基于禁忌表重访限制机制和领域结构的智能组合, 高效地完成了卫星观测调度问题. 
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表 2 单星地面离线任务调度规划系统
Table 2 Single-satellite offline task scheduling system
调度规划系统 调度规划策略与方法 系统实际应用场景 SPIKE调度系统[39] 启发式调度规划方法 NASA的哈勃太空望远镜 ASPEN系统 局部提前规划, 迭代搜索 NASA的深空一号DS-1和对地观测EO-1 APSI系统 基于时间线的方法 欧洲太空局ESA 在时间层管理任务时间网络 MAPGEN系统 在简单时序约束网络上, 将混合主动式任务规划与约束规划框架相结合 火星探测器项目
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表 3 单星星上在线任务调度规划系统
Table 3 Single-satellite online task scheduling system
调度规划系统 调度规划策略与方法 系统实际应用场景 RAX-PS系统 启发式调度规划方法 NASA的哈勃太空望远镜 ASE环境、CASPER系统 连续性规划 NASA对地观测EO-1 迭代修复 TechSat-2 采用局部搜索进行计划渐次精细化 AGATA 在线决策的反应型/慎重型架构 法国灵巧对地观测Pleiades卫星 反应型部分采用决策规则 慎重型部分采用迭代随机贪婪搜索算法
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表 4 单星地面离线调度与单星在线调度的优势比较
Table 4 The comparison of the advantages between single-satellite offline task scheduling and onboard task scheduling
单星地面离线自主调度规划 星上在线自主任务调度规划 可用的CPU计算处理能力强大 软件更改灵活性强 对环境响应速度快 测试过程不影响星上任务执行 在无通信延迟的情况下处理图像数据 与操作员和用户的交互及时快捷 减少星地之间的通信交互次数 软件开发成本低
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表 5 多星地面离线任务调度规划系统
Table 5 Multi-satellite ground offline task scheduling system
调度规划系统 调度规划策略与方法 系统实际应用场景 SpaceCAPS系统 分为星座、星群和单个卫星三个层次上的规划 TechSat21计划 构造算法与迭代修正方法相结合 PLANET系统 支持任务动态重规划 MUSIS项目
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表 6 多星星地一体化协同任务调度规划系统
Table 6 Multi-satellite and ground integrated task scheduling system
调度规划系统 调度规划策略与方法 系统实际应用场景 DIPS系统 采用分散的架构 3CSAT星座 层次任务分解 层次化的确认/授权机制 基于优先级的调度算法
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