敏捷光学卫星密集区域推扫成像任务规划方法

敏捷成像卫星可以实现利用三轴姿态机动所形成的推扫成像模式,同时可以在机动过程中同步成像。在敏捷卫星成像任务的基础上,建立考虑推扫成像模式的敏捷卫星任务规划模型。通过高斯投影建立球面直线扫描条带的数学生成模型,并利用Matlab现有函数进行优化解算;由于模型解算的复杂性,将整体规划问题分为两层子问题分别进行处理,在条带任务分配中,设计了适用于计算机计算的含有条带分配策略的解算算法;在上层规划中,基于推扫成像的双向扫描特性,设计了基于启发式规则的敏捷卫星任务规划算法;之后,将不可规划条带拆作孤立点目标进行处理,最后通过再合成处理完成整体规划。仿真结果表明,文章所设计的算法可以有效处理实际情况下的敏捷卫星推扫成像任务规划问题。     

面向海洋观测的成像卫星任务规划方法

面向海洋观测的成像卫星是一种轨道较高的可见光对地观测卫星,主要用于探测海上船舶活动以及监测海洋环境参数等。对地观测卫星任务规划问题是一个复杂的组合优化问题,通过分析面向海洋观测的成像卫星工作特点及约束条件,建立了一种考虑多数传模式共存的数学模型,提出了一种基于最大收益损失比的卫星任务规划算法。试验结果表明该方法能够有效解决面向海洋观测的成像卫星任务规划问题。     

多星联合任务规划方法

针对多星对地观测系统联合任务规划问题,考虑卫星载荷具备连续侧摆能力和多种数据压缩模式的新特点,构建了多星联合任务规划模型,在此基础上设计多星联合任务规划和数传调度算法框架,实现了卫星连续侧摆成像规划算法和基于任务优先级的数传任务调度算法,最后采用实际算例进行试验,结果表明文章提出的多星联合任务规划方法能在提高完成任务数量的同时降低卫星资源消耗,满足实际应用需求。     

Mission planning optimization of video satellite for ground multi-object staring imaging

This study investigates the emergency scheduling problem of ground multi-object staring imaging for a single video satellite. In the proposed mission scenario, the ground objects require a specified duration of staring imaging by the video satellite. The planning horizon is not long, i.e., it is usually shorter than one orbit period. A binary decision variable and the imaging order are used as the design variables, and the total observation revenue combined with the influence of the total attitude maneuvering time is regarded as the optimization objective. Based on the constraints of the observation time windows, satellite attitude adjustment time, and satellite maneuverability, a constraint satisfaction mission planning model is established for ground object staring imaging by a single video satellite. Further, a modified ant colony optimization algorithm with tabu lists (Tabu-ACO) is designed to solve this problem. The proposed algorithm can fully exploit the intelligence and local search ability of ACO. Based on full consideration of the mission characteristics, the design of the tabu lists can reduce the search range of ACO and improve the algorithm efficiency significantly. The simulation results show that the proposed algorithm outperforms the conventional algorithm in terms of optimization performance, and it can obtain satisfactory scheduling results for the mission planning problem.     

Closed-form solution of attitude command generation for spin-to-spin maneuver

In recent earth observing missions, agile satellites enable various imaging modes beyond the traditional along-track strip imaging. However, it requires maneuvering with boundary conditions of considerable angular velocity, i.e., spin-to-spin maneuvering. This paper proposes an attitude command generation method for spin-to-spin maneuvering that can provide feedforward commands for the attitude control loop. A general solution for arbitrary flight time is provided which steers a satellite to the given final attitude and angular velocity at the prescribed time. In addition, an alternative method is proposed that further improves the maneuvering speed, which is applicable to small-angle maneuvering cases. The proposed solutions are both closed-form which are more intuitive and easier to comprehend than numerical solutions. It also has a great advantage in computational efficiency, which could enable its use on-board in real time. Numerical examples demonstrate the performance of the proposed methods in a single maneuvering case as well as in a consecutive maneuvering case integrated with a realistic earth observing scenario.     

量子科学实验卫星密钥分发实验任务规划

针对量子科学实验卫星密钥分发实验任务规划约束条件多以及时效性要求高的特点，基于对密钥分发实验过程及约束分析，建立了约束满足规划模型.以完成时限最短为优化目标，综合考虑任务规划所需光学及数传站资源分配，利用深度优先搜索算法对模型进行求解，解决了实验过程中多要素紧耦合、强时间约束的难题.仿真分析结果表明，所提出的模型及算法有效，能够满足量子科学实验卫星密钥分发实验星地交互的需求.      

对地观测卫星有限推力快速轨道机动优化方法

研究了对地观测卫星在有限推力作用下,快速轨道机动到目标区域上空的优化算法.分析了任务需求并选取两次点火的变轨方法,使算法更具普适性.推导出考虑J2摄动的三维空间的有限推力动力学方程.使用Lambert方法确定有限推力时间变量的取值范围,并在此基础上使用遗传算法进行优化,最终得到时间最优意义的优化结果.通过一个算例对整个优化算法做了验证.结果表明该算法精度高、计算时间短,适用于快速轨道机动任务.      

面向卫星多目标重复观测任务的分层聚类规划

针对敏捷卫星多目标重复观测任务规划面临的可行任务执行序列集合规模庞大困难,提出了一种任务执行序列时间解耦的分层聚类任务规划方法。该方法以规划过程中的可观测窗口和任务执行窗口为聚类对象,通过单次可观测窗口聚类和多次任务执行窗口聚类将任务集合按任务窗口属性分解为一系列时间解耦的小规模集合,在两次任务执行窗口聚类间使用基于贪婪优化的搜索算法对聚类生成的小规模任务集合分别进行集合内任务规划,最后将各集合的任务规划结果合并后得到所有任务的执行序列。仿真结果表明,该分层聚类方法可有效降低全局优化复杂度,消解不同优先级观测任务的冲突,提高任务规划质量,能够在不降低目标点观测完成率的前提下对有多个观测机会的目标点进行重复观测,且算法稳定性好,能在数秒内得出规划结果,适用于星上自主任务规划。     

中继卫星单址链路调度模型与算法研究

中继卫星的任务规划与调度是空间资源管理的重要内容之一,目的在于为中继卫星系统的任务计划编制提供科学合理的决策手段与依据。中继卫星单址链路调度问题的重要特点在于,中继卫星与用户航天器之间并非时时可见,因此通信任务存在可见时间窗口约束。只有在可见时间窗口内,通信任务才可能执行并完成。在进行合理假设的基础上,建立中继卫星单址链路调度问题的约束规划模型。对基本遗传算法进行改进,提出了基于有效基因路径表示的改进遗传算法。应用结果表明,基于约束规划理论建立中继卫星单址链路调度模型并采用基于有效基因路径表示的遗传算法求解是合理的。     

异构计算系统中独立任务调度的混合遗传算法

有效的任务调度是异构计算系统获取高性能的关键因素之一,由于任务调度问题是NP-困难的,为了获取尽可能好的解,文献中存在许多启发式调度算法.针对异构计算系统的独立任务调度问题,基于遗传算法和最小完成时间算法MCT(Minimum Completion Time),提出一种新的混合遗传算法,它采用遗传算法来进化任务调度的优先队列,然后再使用MCT算法把优先队列解码为一个有效的调度,与文献中其它算法进行比较表明,它不但能产生更好的调度结果,而且有很好的收敛速度.      

天基信息港的多源信息融合任务调度研究

在天基信息港上实现多源信息融合,可以将数据的传输与处理集中在星上,减少了数据处理中心接收和分发数据的传输时间,提高了信息获取的时效性。考虑到任务高时效性的需求及天基信息港的资源受限,文章提出了天基信息港的多源信息融合任务调度问题,通过分析多源信息融合任务流程、天基信息港的资源特征,以最小化任务完成时间为优化目标,建立了天基信息港的多源信息融合任务调度模型,并设计了一种多机循环插入（Multi-machine Circular Insertion,MCI）算法对模型求解。仿真结果表明,该算法相比于列表调度算法能够平均减少10.8%的任务完成时间,算法运行时间大约为遗传算法的1/20,表明该算法能够满足天基信息港任务调度的高时效性要求。     

月地双基SAR成像的快速后向投影算法研究

为了提高对全球变化的大尺度观测能力,月基对地观测的概念应运而生。由于月基单站合成孔径雷达（Synthetic Aperture Radar,SAR）的双程传播会造成回波信噪比衰减,为此针对月地双基SAR工作模式展开研究。考虑到月、地、星复杂的相对运动为成像带来困难,根据月、地、星的几何关系建立平面直角回波模型。同时考虑到月球和卫星运行轨迹的弯曲性,分析模型误差,推导了精确的回波二维频谱表达式。在此基础上提出了一种基于快速后向投影的SAR成像算法,补偿了方位空变的模型误差,利用频域子孔径成像和频谱融合实现成像算法的快速化。通过分析可知月地双基SAR的理论回波信噪比与地月距离的平方成反比,与月基单站SAR相比有显著提升,最后通过X波段SAR仿真数据验证了文章算法处理月地双基SAR成像问题的效性。     

基于有向无圈图的敏捷卫星姿态机动策略

针对敏捷卫星一次过境时间内的同轨拼幅观测和同轨多点连续观测模式的姿态机动策略问题,提出一种基于时间序有向无圈图的敏捷卫星姿态机动策略算法.该算法首先将区域目标和点目标转化为若干条带目标,然后通过将各个条带的观测时间窗口离散成一系列带有条带信息的时刻点,构造时间序有向无圈图,将敏捷卫星对地观测姿态机动策略问题转换为图论的寻找最优路径问题.仿真算例表明,该算法能够有效解决敏捷卫星同轨拼幅观测和多点连续观测的姿态机动策略问题,获得最大化观测覆盖收益同时机动时间消耗最小的姿态机动方案.      

Generation of satellite tracking profile: Problems and validation algorithms

Recently, as a satellite mission becomes complicated, it has been required to generate the schedule of satellite antenna movements automatically without relying upon operator’s ad hoc knowledge. To generate the satellite antenna schedule autonomously, this paper first addresses geometrical problems associated with the antenna scheduling and mission planning problems that can be formulated from satellite navigation and antenna orientation information. Then, based on the solutions of the geometrical problems, a set of antenna azimuth and elevation angles that enables the antenna to point towards the desired ground station is obtained systematically. Using the computed azimuth and elevation angles, the satellite tracking profile (TP) is generated, and to validate it, TP validation algorithms are developed.     

应用于卫星自主任务调度的改进遗传算法

针对具有侧摆能力的对地观测卫星的自主任务调度问题,对卫星自主任务调度问题和约束条件进行了描述,针对卫星自主任务调度NP-hard的特点,构建了基于目标收益及多约束卫星任务调度模型。设计了一种改进的遗传算法,从遗传操作的各个部分进行算法优化。首先将小区间法应用于初始种群生成,保证了种群的多样性,并且交叉和变异算子均引入自适应概率;同时采用两代竞争技术来避免“早熟”现象,提高算法的效率和鲁棒性。算法还采用最优保留策略用来保存进化中的最优解,使得算法收敛于全局最优。对局部多冲突观测任务应用该改进遗传算法,并针对区域密集目标的观测问题设计了仿真试验,与传统模拟退火算法及免疫蚁群遗传混合算法进行了比较,验证了该算法的有效性和收敛效果。     

ARINC 653分区实时系统的主时间框架设计

综合模块化航空电子系统中的ARINC 653标准规定系统采用分区内调度和分区间调度双层调度机制。根据标准,分区内的调度由分区设计者指定,分区之间则按照静态的主时间框架进行调度。如何基于多个分区应用设计用于分区间调度的主时间框架是系统集成阶段需要解决的问题。首先利用可调度分析导出了分区的有界延迟模型参数,进一步将该参数转化为分区的调度参数用于分区间调度。然后进行分区间调度生成主时间框架,提出了最少窗口数目匹配-最佳匹配（MFBF）算法用于减少分区窗口的切换次数。提出的从分区参数推导到分区间调度流程能够基于若干分区应用生成ARINC 653系统的主时间框架。实验结果表明:时间窗口优化算法能有效减少分区窗口切换次数。      

基于Kalman滤波器的卫星钟实时异常监测算法

基于卫星钟钟差的Kalman滤波器模型,提出了一种卫星钟实时异常监测算法,对算法原理进行了讨论,并利用IGS精密钟差数据,对算法进行了性能验证。结果表明：该算法对卫星钟的异常情况（包括单点相位跳变与连续相位跳变）可以进行有效监测,同时还可以完成异常数据的剔除与替换,并且具有较小的替换误差。该算法具有显著的实时性,可以应用于星载原子钟的实时异常监测中。     

Scheduling algorithms for rapid imaging using agile Cubesat constellations

Distributed Space Missions such as formation flight and constellations, are being recognized as important Earth Observation solutions to increase measurement samples over space and time. Cubesats are increasing in size (27U, ～40?kg in development) with increasing capabilities to host imager payloads. Given the precise attitude control systems emerging in the commercial market, Cubesats now have the ability to slew and capture images within short notice. We propose a modular framework that combines orbital mechanics, attitude control and scheduling optimization to plan the time-varying, full-body orientation of agile Cubesats in a constellation such that they maximize the number of observed images and observation time, within the constraints of Cubesat hardware specifications. The attitude control strategy combines bang-bang and PD control, with constraints such as power consumption, response time, and stability factored into the optimality computations and a possible extension to PID control to account for disturbances. Schedule optimization is performed using dynamic programming with two levels of heuristics, verified and improved upon using mixed integer linear programming. The automated scheduler is expected to run on ground station resources and the resultant schedules uplinked to the satellites for execution, however it can be adapted for onboard scheduling, contingent on Cubesat hardware and software upgrades. The framework is generalizable over small steerable spacecraft, sensor specifications, imaging objectives and regions of interest, and is demonstrated using multiple 20?kg satellites in Low Earth Orbit for two case studies – rapid imaging of Landsat’s land and coastal images and extended imaging of global, warm water coral reefs. The proposed algorithm captures up to 161% more Landsat images than nadir-pointing sensors with the same field of view, on a 2-satellite constellation over a 12-h simulation. Integer programming was able to verify that optimality of the dynamic programming solution for single satellites was within 10%, and find up to 5% more optimal solutions. The optimality gap for constellations was found to be 22% at worst, but the dynamic programming schedules were found at nearly four orders of magnitude better computational speed than integer programming. The algorithm can include cloud cover predictions, ground downlink windows or any other spatial, temporal or angular constraints into the orbital module and be integrated into planning tools for agile constellations.     

A scheduling strategy to inter-satellite links assignment in GNSS

By introducing inter-satellite link (ISL), the dependence of the global navigation satellite system (GNSS) on ground infrastructure can be reduced and its performance enhanced via inter-satellite ranging and communication. Owing to platform restrictions, there are usually fewer onboard Ka-band ISL antennas than the number of visible satellites, which poses a problem when optimizing the inter-satellite links assignment of the GNSS. In this study, to optimize inter-satellite ranging and communication, a multi-objective optimization model is built and a scheduling strategy is proposed for the inter-satellite links assignment scheduling problem. The position dilution of precision (PDOP) of links and the transmission time-delay of telemetry data are set as the ranging performance and communication metrics, respectively. We regard the links assignment in each slot as a general graph-matching problem, and apply the Blossom algorithm to obtain the maximum matching. We then generate and optimize the satellite sequences for whole slots using non-dominated sorting genetic algorithm II (NSGA-II). The simulation scenes include 10,080 epochs of GNSS constellation, and the simulation results show that the performance of the proposed strategy is better than that of other methods published recently, and can provide various solutions to meet the different preferences of system managers.     

最小数据丢失量的地月中继卫星任务调度研究

月球背面的探测器必须依靠地月中继卫星进行数据传输与通信。地月中继任务包括实时性任务和延迟容忍类任务，如数传任务。当探测器等待传输的数据量超出用户存储容量时，延迟容忍类任务会由于探测器本地存储资源不足和地月中继卫星天线资源受限而无法完成，导致任务数据丢失，所以需要设计一种合理的地月中继任务调度策略，提高地月中继卫星的资源利用率，减少数据的丢失。对地月中继卫星任务调度进行了研究，在分析地月中继卫星数传任务的特点及用户的存储限制的基础上，以最小化数据丢失量为优化目标，建立了地月中继卫星任务调度模型，并设计了一种基于离散烟花算法（DFWA）的地月中继卫星任务调度算法。仿真数据分析表明，基于离散烟花算法的地月中继卫星任务调度算法在求解结果上优于遗传算法，是一种合理、有效的调度方法。