复杂动态环境下无人飞行器动态避障近似最优轨迹规划

针对复杂动态环境下无人飞行器的动态障碍规避问题，基于合理假设建立了无人飞行器和动态障碍的运动学模型，并综合考虑无人飞行器飞行过程中的终端约束、控制输入约束、安全避障约束等，以能量最少为性能指标构建动态避障问题数学描述。之后，针对终端约束和控制输入约束，依据优化模型预测静态规划算法(OMPSP)生成初始轨迹；针对动态避障问题的不等式约束，引入松弛变量并结合滑模变结构控制方法设计松弛变量动力学，实现对一个、多个或同时多个动态障碍的安全规避；最后，依据有限时间微分动态规划(RHDDP)算法进行轨迹优化，获得满足上述各种约束并能规避动态障碍的近似最优轨迹。     

A survey of safety separation management and collision avoidance approaches of civil UAS operating in integration national airspace system

Recent years have witnessed a booming of the industry of civil Unmanned Aircraft System (UAS). As an emerging industry, the UAS industry has been attracting great attention from governments of all countries and the aviation industry. UAS are highly digitalized, informationized, and intelligent; therefore, their integration into the national airspace system has become an important trend in the development of civil aviation. However, the complexity of UAS operation poses great challenges to the traditional aviation regulatory system and technical means. How to prevent collisions between UASs and between UAS and manned aircraft to achieve safe and efficient operation in the integrated operating airspace has become a common challenge for industry and academia around the world. In recent years, the international community has carried out a great amount of work and experiments in the air traffic management of UAS and some of the key technologies. This paper attempts to make a review of the UAS separation management and key technologies in collision avoidance in the integrated airspace, mainly focusing on the current situation of UAS Traffic Management (UTM), safety separation standards, detection system, collision risk prediction, collision avoidance, safety risk assessment, etc., as well as an analysis of the bottlenecks that the current researches encountered and their development trends, so as to provide some insights and references for further research in this regard. Finally, this paper makes a further summary of some of the research highlights and challenges.     

基于蚂蚁算法的星上ATM交换结构

对于卫星ATM交换系统，星上ATM交换结构的设计是一个非常重要的部分。由于卫星通信具有带宽有限、时延受限、信道误码率高等特点，因而设计星上交换结构时必须尽可能降低交换时延，减少内部阻塞。为此，提出一种基于蚂蚁算法的星上ATM交换结构，并对此方案进行了分析和仿真。结果表明，该结构由于采用了蚂蚁算法和阻塞规避方案，有效改善了信元时延和信元丢失率等性能。     

月球着陆器精确定点及安全着陆技术研究

在未来月球探测中,需要对一些地形复杂的区域进行探测,而在这些区域软着陆,潜在的危险性增加,这就要求着陆时具有较高的定位精度并能够自动避险。当前,由于着陆时定点的误差较大,在小范围安全地域准确着陆很难。研究了一种精确定位、安全的软着陆方式,它在软着陆过程中增加了悬停阶段。在这一阶段中,通过着陆区危险地域的识别、着陆地点位置误差的计算,加上对着陆器横向漂移的控制技术,使着陆地点的精度以及着陆生存率大为提高,能够满足未来月球探测的软着陆要求。     

Space traffic control: a view of the future

This paper provides an overview of a system for providing reliable, ongoing, timely situational awareness services to satellite operators. Such services would include close approach warnings, warnings of potential radio frequency interference, and other offerings designed to help make operators aware of possible threats to the safe operation of their spacecraft and measures they can take to lessen these threats. The paper discusses current trends, proposes operational requirements, and speculates on the type of organization that may emerge to provide space traffic control services. It highlights how the detailed information required for such services may affect the evolution of the use of space.     

一种新的综合TF／TA最优航迹算法

综合ＴＦ／ＴＡ是新一代低空突防技术，ＴＦ／ＴＡ最优航迹的计算是其控制系统的核心。文中提出了一种新的综合ＴＦ／ＴＡ最优航迹算法，它用动态规划和树型搜索相结合的方法，实时计算综合ＴＦ／ＴＡ最优航迹。算法考虑了飞机机动能力的约束，使最优航迹在不需要平滑处理时就是一个可实现航迹。另外还考虑了威胁的影响，使最优航迹能有效地进行威胁回避。计算结果表明，所得的最优航迹具有综合地形跟踪／回避和威胁回避的能力。     

航空事故人为因素多模型集成分析与控制策略

人为因素是现代航空事故最主要的致因因素,分析航空事故中人为因素的特点,进一步提出预防措施,有利于提高飞行安全水平,实现本质安全。提出多模型集成的航空事故人为因素分析与控制流程,将事故树分析方法( FTA)和人因分析及分类系统( HFACS)相结合,寻找事故的直接原因和深层次原因,全面识别航空事故中的人为因素、事故机理及事故演化过程;运用定量方法找出关键因素,针对性地提出避免由人为因素导致航空事故的策略;根据关联危害性分析法,挖掘事故的潜在不安全因素,实现主动的事故预防。     

A new steering approach for VSCMGs with high precision

A new variable speed control moment gyro (VSCMG) steering law is proposed in order to achieve higher torque precision. The dynamics of VSCMGs is established, and two work modes are then designed according to command torque:control momentum gyro (CMG)/reaction wheel (RW) hybrid mode for the large torque case and RW single mode for the small. When working in the CMG/RW hybrid mode, the steering law deals with the gimbal dead-zone nonlinearity through compensation by RW sub-mode. This is in contrast to the conventional CMG singularity avoidance and wheel speed equalization, as well as the proof of definitely hyperbolic singular property of the CMG sub-mode. When working in the RW single mode, the motion of gimbals will be locked. Both the transition from CMG/RW hybrid mode to RW single mode and the reverse are studied. During the transition, wheel speed equalization and singularity avoidance of both the CMG and RW sub-modes are considered. A steering law for the RWs with locked gimbals is presented. It is shown by simulations that the VSCMGs with this new steering law could reach a better torque precision than the normal CMGs in the case of both large and small torques.     

无人机系统的安全性与危险源分析

无人机系统的战术性能及优势将使其在未来高技术战争和民用航空中发挥越来越重要的作用。然 而,由于有人机与无人机飞行事故的特点不同,使得有人机的安全性分析与管理措施不完全适用于无人机系 统。首先,对无人机系统的飞行事故进行统计分析,得出无人机系统事故的特点;然后,合理借鉴有人机的安全 性分析,定义无人机系统的安全性,提出无人机系统事故的严酷度等级划分及相应的危险可接受度;最后,从设 计、机组训练及使用操作三方面进行危险源分析。本文提出的无人机系统不安全事件发生可能性等级划分和 危险源定性分析,可为后续无人机安全管理框架的构建奠定基础。     

A strategic flight conflict avoidance approach based on a memetic algorithm

Conflict avoidance （CA） plays a crucial role in guaranteeing the airspace safety. The cur- rent approaches, mostly focusing on a short-term situation which eliminates conflicts via local adjust- ment, cannot provide a global solution. Recently, long-term conflict avoidance approaches, which are proposed to provide solutions via strategically planning traffic flow from a global view, have attracted more attentions. With consideration of the situation in China, there are thousands of flights per day and the air route network is large and complex, which makes the long-term problem to be a large-scale combinatorial optimization problem with complex constraints. To minimize the risk of premature convergence being faced by current approaches and obtain higher quality solutions, in this work, we present an effective strategic framework based on a memetic algorithm （MA）, which can markedly improve search capability via a combination of population-based global search and local improve- ments made by individuals. In addition, a specially designed local search operator and an adaptive local search frequency strategy are proposed to improve the solution quality. Furthermore, a fast genetic algorithm （GA） is presented as the global optimization method. Empirical studies using real traffic data of the Chinese air route network and daily flight plans show that our approach outper- formed the existing approaches including the GA .based approach and the cooperative coevolution based approach as well as some well-known memetic algorithm based approaches.