基于单目三维重构的空间非合作目标相对测量

为了解决非合作目标的相对测量问题,提出了一种基于单目图像序列目标重构结果的非合作目标相对位姿测量方法。该方法将目标的三维重构与相机的位姿信息计算相结合,首先利用观测前期得到的图像序列,通过非线性优化算法计算得到目标上部分三维点坐标;然后基于该三维点集合,建立递推深度模型,对相机的相对位姿信息和新观测到的目标点同时进行卡尔曼滤波估计。航拍测量试验表明,随着图片数量的增多,精确重构点的比例（重投影误差小于1个像素的点）不断提高,80%的图像中精确重构点比例优于89%;基于公共数据集的试验表明,该算法对姿态估算精度可达1°以内,位置测量的精度可达到2cm以内。以上试验结果表明,该算法具有较高的测量精度。     

Toward a global space exploration program: A stepping stone approach

In response to the growing importance of space exploration in future planning, the Committee on Space Research (COSPAR) Panel on Exploration (PEX) was chartered to provide independent scientific advice to support the development of exploration programs and to safeguard the potential scientific assets of solar system objects. In this report, PEX elaborates a stepwise approach to achieve a new level of space cooperation that can help develop world-wide capabilities in space science and exploration and support a transition that will lead to a global space exploration program. The proposed stepping stones are intended to transcend cross-cultural barriers, leading to the development of technical interfaces and shared legal frameworks and fostering coordination and cooperation on a broad front. Input for this report was drawn from expertise provided by COSPAR Associates within the international community and via the contacts they maintain in various scientific entities. The report provides a summary and synthesis of science roadmaps and recommendations for planetary exploration produced by many national and international working groups, aiming to encourage and exploit synergies among similar programs. While science and technology represent the core and, often, the drivers for space exploration, several other disciplines and their stakeholders (Earth science, space law, and others) should be more robustly interlinked and involved than they have been to date. The report argues that a shared vision is crucial to this linkage, and to providing a direction that enables new countries and stakeholders to join and engage in the overall space exploration effort. Building a basic space technology capacity within a wider range of countries, ensuring new actors in space act responsibly, and increasing public awareness and engagement are concrete steps that can provide a broader interest in space exploration, worldwide, and build a solid basis for program sustainability. By engaging developing countries and emerging space nations in an international space exploration program, it will be possible to create a critical bottom-up support structure to support program continuity in the development and execution of future global space exploration frameworks. With a focus on stepping stones, COSPAR can support a global space exploration program that stimulates scientists in current and emerging spacefaring nations, and that will invite those in developing countries to participate—pursuing research aimed at answering outstanding questions about the origins and evolution of our solar system and life on Earth (and possibly elsewhere). COSPAR, in cooperation with national and international science foundations and space-related organizations, will advocate this stepping stone approach to enhance future cooperative space exploration efforts.     

China’s Aviation Industry: a Global Partnership Strategy

This article discusses one of the main strategies which China has implemented to develop its competency in the aviation field. It is strategic for China to boost its aviation industry via international cooperation and several models of involvement into the global aviation value chain with leading aviation industries. As it is depicted as a strategy here, it is not necessary to say that a formal strong national strategy in encouraging exists. Actually, it is clearly a way China’s aero industry takes to develop its competency and business at the context it encounters. From an observer’s perspective, it is indeed a critical strategy. This article describes this strategy via the context, policies, program cases, as well as the evolution of the cooperation models in order to synthesize the strategy.     

高职院校实施工学结合人才培养模式面临的问题与对策

工学结合是高职教育改革与发展的方向,工学结合人才培养模式是高职教育的生命线。大力推进校企合作、创新实践工学结合人才培养模式的有效实施方案、探索适合高职院校发展的新思路,是实现高职院校服务社会需求的重要任务。本文分析了我国高等职业教育工学结合的现状及其影响因素,以西安航空职业技术学院为例构建了工学结合人才培养模式的运行体系,提出了实施工学结合的实践策略。     

“国际空间站”建造十年经验初探

就＂国际空间站＂边建造、边应用十年来所获得的经验与教训,从系统设备、居住环境、物资补给、作息制度、健康保障、人的作用、出舱活动及国际合作8个方面进行了简要的论述,对后来的空间站建设及未来的长期载人航天飞行具有重要的参考价值。     

国家社会经济发展的国际比较与评价

提出了正确评价中国社会的发展和进步是很重要的，简要介绍了国际组织，学者进行国际比较所采和的几种主要方法，着重介绍了用社会进步指数方法来确定１９８０年、１９８６年中国在亚洲的地位，社会进步指数包括七个方面的１９年指标，用非加权和加权两种方法分别计算各国的社会进步指数，在计算加权的社会进步指数中采用了主分量分析方法来确定权数，该方法避免了人们的主观因素，提高了计算的准确度，非加权方法的计算结果表明，中     

边缘网络下多无人机协同计算和资源分配联合优化策略

针对边缘网络环境下多人机之间存在计算负载不均，造成卸载任务失败的问题，提出了一种多无人机间协作的智能任务卸载方案。通过联合考虑多无人机任务分配、计算资源分配和无人机飞行轨迹，引入公平性指数建立了无人机公平负载最大化和能量消耗最小化问题。基于多智能体深度强化学习框架，提出了融合轨迹规划和任务卸载的分布式算法。仿真结果表明，所提出的多无人机协作方案可以显著提高任务完成率和负载公平度，并且有效适用于大规模用户设备场景。     

基于改进狼群算法的多无人机协同多目标分配CSCD

针对现代空战多无人机协同多目标任务分配问题,结合标准狼群算法,提出了一种改进狼群算法的多目标任务分配方法。根据狼群的不同分工以及搜索属性,建立了基于自主游走机制的头狼产生规则、基于多策略知识库的探狼游走机制和基于自适应步长的猛狼奔袭及围攻方式,从而对传统狼群算法的随机性进行智能化约束与控制,以解决多无人机协同多目标任务分配问题。数值仿真结果表明,该方法能够快速有效获得任务分配方案,避免陷入局部最优。     

航空公司欧美国际航线运营持续时间生存分析

航空公司航线进入后的运营可持续性直接影响其盈利水平。基于生存分析方法探究影响航线运营持续时间的因素，从成本和供给特征、航线和机场特征、市场结构特征、航司合作类型和时间异质性5个方面选取关键因素，以自由化程度较高的欧美跨大西洋市场为实证对象，研究年份为2003—2021共19年，采用Kaplan-Meier方法进行单因素分析，并构建威布尔参数生存模型分析影响因素与航线运营持续时间的定量关系。结果表明：（1）航司在欧美航线的平均运营持续时间为5年，持续运营超过10年的航线占比为16%;(2)距离、航司投入总运力、航线结构、端点机场类型和竞争程度、航司类型及所属区域和联盟对航司航线运营持续时间具有显著影响；（3）联盟和代码共享独立变量和交互变量均对航线生存产生显著影响，星空和天合联盟成员的航线运营持续时间更长，联盟成员在代码共享合作时承担不同承运人角色对航线退出风险影响存在显著差异。     

Improving multi-target cooperative tracking guidance for UAV swarms using multi-agent reinforcement learning

Multi-Target Tracking Guidance(MTTG) in unknown environments has great potential values in applications for Unmanned Aerial Vehicle(UAV) swarms. Although Multi-Agent Deep Reinforcement Learning(MADRL) is a promising technique for learning cooperation, most of the existing methods cannot scale well to decentralized UAV swarms due to their computational complexity or global information requirement. This paper proposes a decentralized MADRL method using the maximum reciprocal reward to learn cooper...