对地观测卫星调度的混合整数规划模型及求解

首先简要介绍对地观测卫星的成像过程,详细分析多星调度过程中涉及的各种约束。在此基础上,将对地观测卫星调度问题看作一类具有时间窗口的并行机器调度问题,对其进行了数学描述,并建立对地观测卫星调度的混合整数规划模型。采用列生成法,将多卫星调度问题分解为集合分割主问题和单卫星调度子问题,通过循环迭代来求解调度模型。最后,针对本文提出的算法设计一个问题实例,并给出算法计算结果。结果分析表明,列生成法的效率与问题规模大小相关。     

成像观测卫星多星联合调度模型及其列生成求解算法研究

首先介绍成像观测卫星调度问题的特点和主要约束,将成像观测卫星调度分为调度预处理、调度模型及求解、调度结果评估3个阶段。在此基础上,论述成像观测卫星调度模型,并采用列生成法,将多卫星调度问题分解为集合分割主问题和单卫星调度子问题,通过循环迭代来求解调度模型。最后,针对本文提出的算法设计一个问题实例,并给出算法计算结果。结果分析表明,本文提出的模型和算法能较好解决实际应用问题。     

人工智能在卫星任务规划中的应用

智能规划与调度是实现卫星自主规划其飞行任务的关键。将人工智能方法应用于卫星的任务规划,以执行对地观测任务为例,将任务规划问题归于组合优化问题,建立了相应的数学模型,并应用Hopfield神经网络算法进行求解,结果表明,该方法可用于单个仪器的任务规划。     

考虑任务合成的成像卫星调度问题

某些成像卫星的侧摆机动性能较差,限制了卫星的观测能力,需要考虑任务合成以提高观测效率.建立了考虑任务合成的成像卫星调度问题模型,并提出了求解该模型的快速模拟退火算法(VFSA).算法针对元任务及合成任务分别构造邻域,采用合成邻域、分解邻域实现调度过程中任务动态合成操作.采用"冒险"的接受概率和快速退火计划,提高算法的求解速度.采用回火机制及3种分化策略,避免算法陷入局部最优.大规模测试算例验证了算法的效率.     

Measuring the Earth’s Magnetic Field from Space: Concepts of Past, Present and Future Missions

Observations of the Earth’s magnetic field from low-Earth orbiting (LEO) satellites started very early on, more than 50 years ago. Continuous such observations, relying on more advanced technology and mission concepts, have however only been available since 1999. The unprecedented time-space coverage of this recent data set opened revolutionary new possibilities for monitoring, understanding and exploring the Earth’s magnetic field. In the near future, the three-satellite Swarm constellation concept to be launched by ESA, will not only ensure continuity of such measurements, but also provide enhanced possibilities to improve on our ability to characterize and understand the many sources that produce this field. In the present paper we review and discuss the advantages and drawbacks of the various LEO space magnetometry concepts that have been used so far, and report on the motivations that led to the latest Swarm constellation concept. We conclude with some considerations about future concepts that could possibly be implemented to ensure the much needed continuity of LEO space magnetometry, possibly with enhanced scientific return, by the time the Swarm mission ends.     

电磁探测卫星星上自主规划模型及优化算法

电磁探测卫星自治(AEDS)是一类对地观测卫星,其搜集的信息对工业、科研和军事等领域有着重要的意义。针对电磁探测卫星有效载荷特点,建立了基于动态拓扑结构无环路有向图的星上自主规划数学模型,提出了基于标记更新最短路径搜索的星上自主规划精确算法,对其完备性和时间复杂度进行了分析。并对精确算法时间复杂度较高的缺点,将近似支配概念引入到模型中,提出了标记更新最短路径搜索近似算法,分析了算法的近似程度和时间复杂度。最后,根据模拟的数据进行实验及分析,表明该方法能有效解决电磁探测卫星自主任务规划问题。     

多星任务规划中的FFFS-DTMB与ADTPC-DTMB算法

 多星对地观测任务规划是一类典型组合优化问题,针对该问题中常见的时间窗口冲突问题,根据同一时间窗口内的冲突任务的处理方式提出了两种有效处理此类问题的规划算法：带有冲突任务时间窗口后移的先完成先规划算法(FFFS DTMB)以及冲突任务共存性判断算法(ADTPC DTMB),并给出了关键步骤的算法过程与伪代码。完整的卫星任务规划过程包括了约束检查、优先级检查以及任务规划,不考虑任务间关系与优先级,主要研究处理具有时间窗口冲突的任务规划算法。文中给出的两种算法优化目标均为最大化规划任务数量。算法的主要思路是通过采用一个冲突任务替换一个已规划的任务,并将替换任务后移至下一时间窗口或在同一时间窗口内部后移。最终的评价结果显示了两种算法的有效性。     

基于分层控制免疫遗传算法的多卫星联合任务规划方法

 研究面向复杂任务需求的多卫星联合下的任务规划技术,对于提高对地观测系统的保障能力具有重要意义。各种类型的复杂任务需求由于需求特点的差异,使得相对于针对点观测任务的规划更加复杂。在提炼问题特点的基础上,建立了整数规划问题模型,并提出了分层控制免疫遗传算法。该算法采用双层操作,在父层采用遗传操作算子,在子层采用免疫操作算子,并引入基因重组、自适应免疫更新、小生境等机制改进搜索过程。仿真实验表明,分层控制免疫算法在解决复杂任务的任务规划中是可行有效的。     

面向应急条件的多星动态调度方法

 针对应急条件下多星动态调度问题,建立了多目标数学规划模型,提出了应急条件多星成像任务合成策略:建立多星多轨任务合成图(MSMOTMG)模型,提出任务合成算法CP-TM。为克服合成导致任务成像机会减少的缺陷,提出了基于合成任务分解的修复技术。此外,为进一步提高调度效率,考虑了任务在等待队列中的向后移位策略,提出了综合考虑任务合成、修复和向后移位的多星动态应急调度(TMRBS-DES)算法。通过大量模拟实验,将TMRBS-DES算法同RBHA算法,以及3个baseline算法(BS-DES、TMR-DES和TMBS-DES)进行了比较。实验结果表明TMRBS-DES算法提高了调度质量,适用于应急条件下多星动态调度问题。     

Dynamo Models for Planets Other Than Earth

Observations from planetary spacecraft missions have demonstrated a spectrum of dynamo behaviour in planets. From currently active dynamos, to remanent crustal fields from past dynamo action, to no observed magnetization, the planets and moons in our solar system offer magnetic clues to their interior structure and evolution. Here we review numerical dynamo simulations for planets other than Earth. For the terrestrial planets and satellites, we discuss specific magnetic field oddities that dynamo models attempt to explain. For the giant planets, we discuss both non-magnetic and magnetic convection models and their ability to reproduce observations of surface zonal flows and magnetic field morphology. Future improvements to numerical models and new missions to collect planetary magnetic data will continue to improve our understanding of the magnetic field generation process inside planets.     

LEO navigation augmentation constellation design with the multi-objective optimization approaches

Low Earth Orbit (LEO) satellite for navigation augmentation applications can significantly reduce the precise positioning convergence time and attract increasing attention recently. A few LEO Navigation Augmentation (LEO-NA) constellations have been proposed, while corresponding constellation design methodologies have not been systematically studied. The LEO-NA constellation generally consists of a huge number of LEO satellites and it strives for multiple optimization purposes. It is essentially different from the communication constellation or earth observing constellation design problem. In this study, we modeled the LEO-NA constellation design problem as a multi-objective optimization problem and solve this problem with the Multi-Objective Particle Swarm Optimization (MOPSO) algorithm. Three objectives are used to strive for the best tradeoff between the augmentation performance and deployment efficiency, namely the Position Dilution of Precision (PDOP), visible LEO satellites and the orbit altitude. A fuzzy set approach is used to select the final constellation from a set of Pareto optimal solutions given by the MOPSO algorithm. To evaluate the performance of the optimized constellation, we tested two constellations with 144 and 288 satellites and each constellation has three optimization schemes: the polar constellation, the single-layer constellation and the two-layer constellation. The results indicate that the optimized two-layer constellation achieves the best global coverage and is followed by the single-layer constellation. The MOPSO algorithm can help to improve the constellation design and is suitable for solving the LEO-NA constellation design problem.     

WGS-84模型下时差频差半定规划定位算法

利用多颗卫星的时差频差对辐射源进行位置和速度的测量,其本质意义上是一个含有噪声项的高度非线性方程组求解问题,针对地面目标而言,可以采用基于WGS-84地球模型作为目标位置和速度约束,更进一步的增加了定位系统的复杂性。提出了一种基于半定规划(SDP)的定位解算法,将非线性方程求解问题通过适当的松弛,转化为半定优化(SDO)的问题,借助于业界较为成熟的CVX等优化软件进行定位求解,并研究了该模型条件下的克拉美罗下界(CRLB)。仿真结果表明,该算法能够较好地逼近克拉美罗下界。     

First spaceborne demonstration of BeiDou-3 signals for GNSS reflectometry from CYGNSS constellation

The full constellation of Chinese Global Navigation Satellite System (GNSS) BeiDou-3 has been deployed completely and started fully operational service. In addition to providing global Positioning, Navigation and Timing (PNT) services, the BeiDou-3 satellites transmissions can also be used as the sources of illumination for Earth Observation (EO) with a bistatic radar configuration. This innovative EO concept, known as GNSS reflectometry (GNSS-R), allows to measure the Earth surface characteristics at high resolution via the reflected L-band radar signals collected by a constellation of small, low cost and low Earth orbiting satellites. For the first time in orbit, earth reflected BeiDou-3 signal has been detected from the limited sets of raw data collected by the NASA’s Cyclone GNSS (CYGNSS) constellation. The feasibility of spaceborne BeiDou-3 reflections on two typical applications, including sea surface wind and flooding inundation detection, has been demonstrated. The methodology and results give new strength to the prospect of new spaceborne GNSS-R instruments and missions, which can make multi-GNSS reflectometry observations available to better capture rapidly changing weather systems at better spatio-temporal scales.     

基于执行时段滑动调整策略的中继卫星任务规划算法设计

针对中继卫星任务规划问题开展研究,提出一种基于执行时段滑动调整策略的任务规划算法。首先分析了中继卫星资源调度过程,并对任务申请的时间特征进行形式化描述,然后归纳出任务分配的主要约束,从而完成问题建模。在此基础上,对优化算法进行设计,给出了执行时段滑动调整步骤。通过调整已规划任务执行时段的方法,使部分原本无法执行任务具备执行可能,提升了任务执行率和资源利用率。在仿真实验中,通过大规模测试分析对比不同算法的优化效果,验证了文中所提方法的有效性。     

基于混合蚁群算法的柔性模糊车间作业调度

采用蚁群算法作为全局搜索算法,提出一种混合搜索策略,用于求解柔性模糊Job Shop调度问题.根据模糊Job Shop调度问题解的特性,提出基于     

多机场终端区进场交通流优化排序方法研究

为了提高终端区时空资源利用率及空中交通运行效率,综合考虑航班间尾流间隔、航向道安全间隔及定位点管制移交间隔等时间标准的约束,研究了进场交通流在多机场多跑道系统及定位点的排序优化问题,建立了整数线性规划模型,旨在最小化多机场航班的总延迟时间和跑道总调度时长.开发出Epsilon约束精确算法,可以在数分钟内求解出多机场进场交通流排序方案的Pareto前沿.通过仿真实验证明了模型的正确性及算法的有效性.     

嵌入式高可信架构中基于静态模型的调度研究

为解决嵌入式高可信软件架构中的实时调度问题,分析了现有采用分区机制的安全系统中分区调度的不足,提出了一种基于固定周期分区的静态调度模型,并采用优先级位图算法建立了两级调度机制。为了保障分区中任务的实时性和正确性,对分区中任务采用静态优先级和最早时限优先调度(EDF)动态优先级两种调度策略,分别就其任务调度条件和可调度性进行了理论研究,针对复杂的动态优先级任务提出了一种可调度条件,并通过仿真实验进一步验证了此调度条件的正确性。     

21世纪AMSS／GNSS空间段发展方向兼论卫星资源国际共享问题

航空移动卫星系统（ＡＭＳＳ）空间段采用单一的ＧＥＯ轨道卫星，未来将有ＭＥＯ和ＬＥＯ轨道卫星加入运行，仍然不排斥ＧＥＯ轨道卫星的使用。全球导航卫星系统（ＧＮＳＳ）空间段采用ＭＥＯ轨道卫星，未来将仍然以ＭＥＯ为主，可能有ＨＥＯ轨道卫星加入运行。２１世纪的空间段将为不同轨道卫星的多星座组合，采用一星多用、星座共用，形成多功能卫星和多功能星座。和平时期卫星资源的国际民间共建共营共享将更为普遍，要有全球观点，国内各行各业要有全局观点，对监测和增强系统统一筹建共用系统，防止分散投资、重复建设     

考虑任务合成的成像卫星调度问题

某些成像卫星的侧摆机动性能较差,限制了卫星的观测能力,需要考虑任务合成以提高观测效率。建立了考虑任务合成的成像卫星调度问题模型,并提出了求解该模型的快速模拟退火算法(VFSA)。算法针对元任务及合成任务分别构造邻域,采用合成邻域、分解邻域实现调度过程中任务动态合成操作。采用“冒险”的接受概率和快速退火计划,提高算法的求解速度。采用回火机制及3种分化策略,避免算法陷入局部最优。大规模测试算例验证了算法的效率。     

Crosslink slot assignment in LEO networks

The problem of crosslink time slot assignment in low Earth orbiting (LEO) satellite networks is addressed. A crosslink channel connects two neighboring satellites through half-duplexed directional antennas. Coordination among the crosslinks between a satellite and all its neighbors in a dynamic LEO network is a delicate problem and rarely addressed in the literature. The problem is solved here using bipartite graphs. Two versions of slot assignment algorithm are given: distributed and centralized.