低空无人机交通管理概览与建议综述

大量无序飞行的低空无人机运行会对地面设施、公共安全、空中载人飞行器等带来危害。然而,目前民航空中交通管理不能适应未来数以百万架的无人机。为了应对该挑战,世界各国针对低空无人机空中交通管理开发了新框架。低空无人机空中交通管理属于近几年出来的新事物。藉此聚焦于低空无人机交通管理,从4个方面进行概览：低空无人机相关的空中交通基本概念及现状、低空无人机交通管理介绍、低空无人机交通管理的关键技术和低空无人机交通管理相关科学问题,以期望对无人机产业健康发展有一定的建议意义。     

低空反无人机技术现状与发展趋势

近年来,随着无人机技术的不断发展与完善,无人机不仅在军事领域发挥着重要作用,在民用领域也得到了广泛应用。然而,随着使用难度的不断降低,无人机在给人们生产生活带来巨大便利的同时,其"黑飞"与滥用也给国家、社会和人民造成了安全危害。因此,对低空无人机进行反制与防护的需求在军、民领域均十分强烈。围绕无人机在不同领域的应用状况,介绍了低空无人机非合作飞行带来的安全问题,对威胁种类及来源进行了讨论;在此基础上,着重对国内外反无人机技术的发展现状进行了深入分析,对现有反无人机技术体系的组成及相关系统的优缺点进行了综述。此外,结合低空反无人机系统研发的智能化、一体化、自主化问题,分析并讨论了低空反无人机中探测与防护关键技术的未来发展趋势。     

基于粗糙集理论的编队协同空战决策规则提取

为了对空战过程中大量的冗余信息进行约简，以提高空战决策的实时性，将粗糙集理论引入到编队协同空战战术决策研究中，提出了一种用于提取空战关键信息和战术决策规则的属性约简算法。并将单一决策属性下的属性值约简方法推广，讨论了更适于编队作战分析的多决策属性下的属性值约简问题。最后，通过一个编队空战战术选择示例对该算法进行了验证，结果表明：空战的冗余信息是可以约简的；此算法可提取出对空战起主要作用的属性，即雷达／中距弹信息；并且在保证空战关键分类结果不变的情况下，可生成用于战术决策的最小简化策略，所提取的决策规则与编队空战的实际相符合。     

Measuring air traffic complexity based on small samples

Air traffic complexity is an objective metric for evaluating the operational condition of the airspace.It has several applications,such as airspace design and traffic flow management.Therefore,identifying a reliable method to accurately measure traffic complexity is important.Considering that many factors correlate with traffic complexity in complicated nonlinear ways,researchers have proposed several complexity evaluation methods based on machine learning models which were trained with large samples.However,the high cost of sample collection usually results in limited training set.In this paper,an ensemble learning model is proposed for measuring air traffic complexity within a sector based on small samples.To exploit the classification information within each factor,multiple diverse factor subsets (FSSs) are generated under guidance from factor noise and independence analysis.Then,a base complexity evaluator is built corresponding to each FSS.The final complexity evaluation result is obtained by integrating all results from the base evaluators.Experimental studies using real-world air traffic operation data demonstrate the advantages of our model for small-sample-based traffic complexity evaluation over other stateof-the-art methods.     

基于空间多特征综合推理的航迹航路关联

针对航迹分类问题,研究了基于空间多特征的综合推理在航路判读中的应用。首先根据空管系统对航路以及飞机飞行的要求,对航迹航路相关问题进行建模。然后根据已知的传感器系统输出的目标特性(位置,航向)与已知的多个航路信息分别进行相关度计算,构造基本信任函数,通过对其融合,得到目标单特征识别结果。其中,通过合理地引入复合类,实现了对目标类别的广义信任分类。建立了多特征折扣融合算法,对多特征基本信任函数进行折扣后再融合,得到目标多特征识别结果。仿真结果以及空管实际数据测试表明:该算法不仅可以实现航迹分类,同时可以有效地降低分类的错误率。     

空中交通复杂性研究进展

空中交通复杂性是空中交通态势的本质属性，是空中交通管制工作负荷的主要驱动因素。空中交通复杂性的科学评价是实现空中交通精细化管理的关键，也是当前空管领域研究热点。本文介绍了国内外空中交通复杂性的研究团队，梳理了空中交通复杂性与工作负荷、安全水平等相互之间的区别和联系，并详细分析了现有研究的具体研究路线。在分析新一代空中交通管理系统特征的基础上，对空中交通复杂性的未来研究趋势和方向进行了展望。     

终端区飞机排序的规划模型和算法研究

对终端区到达飞机进行排序是终端区交通管理自动化系统的一项主要任务。提出了一种新的终端区规划排序模型，把飞机的排序问题看作等价于带有准备好时间的渐增周游店员问题，并给出了兼顾解的最优性和计算复杂性的快速启发式算法。分析了静态和动态两种情况，并且考虑了实际的运行限制。计算结果表明，所给模型和算法具有良好的规划性能，能较好地解决终端区排序问题，可应用于我国空中战术流量管制系统。     

A heuristic cabin-type component alignment method based on multi-source data fusion

In cabin-type component alignment, digital measurement technology is usually adopted to provide guidance for assembly. Depending on the system of measurement, the alignment process can be divided into measurement-assisted assembly (MAA) and force-driven assembly. In MAA, relative pose between components is directly measured to guide assembly, while in force-driven assembly, only contact state can be recognized according to measured six-dimensional force and torque (6D F/T) and the process is completed based on preset assembly strategy. Aiming to improve the efficiency of force-driven cabin-type component alignment, this paper proposed a heuristic alignment method based on multi-source data fusion. In this method, measured 6D F/T, pose data and geometric information of components are fused to calculate the relative pose between components and guide the movement of pose adjustment platform. Among these data types, pose data and measured 6D F/T are combined as data set. To collect the data sets needed for data fusion, dynamic gravity compensation method and hybrid motion control method are designed. Then the relative pose calculation method is elaborated, which transforms collected data sets into discrete geometric elements and calculates the relative poses based on the geometric information of components. Finally, experiments are conducted in simulation environment and the results show that the proposed alignment method is feasible and effective.     

What is System Wide Information Management (SWIM)?

System wide information management (SWIM) has been identified by the FAA as a key enabler for the next generation air traffic system (NGATS). Boeing has been working with the FAA since 2004 to define the role of SWIM within the framework of the existing and envisioned set of national airspace system (NAS) communications systems and air traffic operations. SWIM, as an information management infrastructure, in effect creates a "system of systems" of existing (and new) systems (or software applications, or simply applications) interacting through SWIM services. Describing SWIM in such a context is only fruitful when adopting the point of view of each person based on their role and perspective of airspace operations, be they a user, an application developed, or a SWIM implemented. This paper describes the current vision of SWIM from multiple viewpoints (operational, functional, physical) in an attempt to provide a broad perspective of SWIM to a technical audience of mixed backgrounds     

Pose matters: Pose guided graph attention network for person re-identification

Person re-Identification (reID), aiming at retrieving a person across different cameras, has been playing a more and more important role in the construction of smart city and social security. For deep-learning-based reID methods, it has been proved that using local feature together with global feature could help to give robust representation for person retrieval. Human pose information can provide the locations of human skeleton to effectively guide the network to pay more attention to these key areas, and can also help to reduce the noise distractions from background or occlusions. Based on human pose, a Pose Guided Graph Attention (PGGA) network is proposed in this paper, which is a multi-branch architecture consisting of one branch for global feature and two branches for local key-point features. A graph attention convolution layer is carefully designed to re-assign the contribution weight of each extracted local feature by modeling the similarity relations. The experimental results demonstrate the effectiveness of our approach on discriminative feature learning. Our model achieves the state-of-the-art performance on several mainstream evaluation datasets. A plenty of ablation studies and different kinds of comparison experiments are conducted to prove the effectiveness of this work, including the tests on occluded datasets and cross-domain datasets. Moreover, we further design supplementary tests in practical scenario to indicate the advantage of our work in real-word applications.     

基于灰色关联聚类的空中交通复杂度评估方法

为了准确评价空中交通态势的复杂程度,进行有效的空中交通管理,提出了一种空中交通复杂度评估方法。在已有的理论研究成果及实际运行经验的基础上,归纳了定义明确、可定量分析的基础空中交通指标集,使用灰色关联聚类方法对指标集进行聚类分析,利用信息熵理论对聚类指标求解权重,加权求和获得空中交通复杂度。方法弥补了目前使用单一维度指标描述空中交通运行态势的弊端,能更好地体现空中交通复杂度。     

用SPH和有限元方法研究鸟撞飞机风挡问题

鸟与飞行中的飞机相撞是飞机结构损坏的重要因素,严重时会引发机毁人亡的灾难性事故。对高速低空飞行的军用飞机而言,风挡部分抗鸟撞的研究对保证飞行安全尤其重要。基于飞机圆弧风挡受鸟体撞击的实验观察,建立了国产某型军用飞机圆弧风挡及鸟体的计算模型,采用LS-DYNA3D中有限元和光滑粒子流体动力学(SPH)耦合的数值分析方法,对某飞机圆弧风挡受鸟体撞击的过程进行了数值模拟。计算结果得到了风挡结构的变形、位移和应变等几方面的数据,与实验结果基本吻合。同时,给出了500～650km/h速度范围内的撞击力和应力时程曲线、风挡发生破坏的临界撞速、圆弧风挡经受鸟体撞击时发生破坏的可能位置及其破坏方式。最后,与鸟体采用任意拉格朗日(ALE)和无网格伽辽金方法(EFG)进行了对比,验证了SPH方法在分析鸟撞问题中的优越性。研究结果为风挡的安全设计和研制新机型提供了有价值的数据。     

空中交通流量管理仿真系统方案研究

随着中国交通流量的不断增长，如何更有效地实施流量管理的问题日益突出。建立空中交通流量管理仿真系统，可以在计算机网络搭建的平台上全面模拟仿真空中交通流量情况，发现存在的问题，寻找合理有效的管理体制和管理方法，为建设流量管理系统提供有力的技术支持。针对流量管理仿真系统的特点，提出系统开发和建设中的总体技术方案和关键技术。     

The thrust and lift of an ornithopter's membrane wings with simple flapping motion

Human beings flying with the help of aircrafts of various kinds have been able to fly for about one century. Although the flapping wings of animals served as an inspiration to pioneers of human flight, we don't really understand how they work. In this study, we employ the concept of four-bar linkage to design a flapping mechanism which simulates a flapping motion of a bird. Wind tunnel tests were performed to measure the lift and thrust of the mechanical membrane flapping wing under different frequency, speed, and angle of attack. It is observed that the flexibility of the wing structure will affect the thrust and lift force due to its deformation at high flapping frequency. The lift force will increase with the increase of the flapping frequency under the corresponding flying speed. For the same flapping frequency, the flying speed can be increased by decrease of the angle of attack with the trade of loosing some lift force. An angle of attack is necessary in a simple flapping motion in order to derive a lift force. The flapping motion generates the thrust to acquire the flying speed. The flying speed and angle of attack combine to generate the lift force for flying.     

Adaptive learning approach to landmine detection

We consider landmine detection using forward-looking ground penetrating radar (FLGPR). The two main challenging tasks include extracting intricate structures of target signals and adapting a classifier to the surrounding environment through learning. Through the time-frequency (TF) analysis, we find that the most discriminant information is TF localized. This observation motivates us to use the over-complete wavelet packet transform (WPT) to sparsely represent signals with the discriminant information encoded into several bases. Then the sequential floating forward selection method is used to extract these components and thereby a neural network (NNW) classifier is designed. To further improve the classification performance and deal with the problem of detecting mines in an unconstraint environment, the AdaBoost algorithm is used. We integrate the feature selection process into the original AdaBoost algorithm. In each iteration, AdaBoost identifies the hard-to-learn examples and a new set of features which provide the specific discriminant information for these hard samples is extracted adaptively and a new classifier is trained. Experimental results based on measured data are presented, showing that a significant improvement on the classification performance can be achieved.     

管制员信息处理能力模糊评价

信息处理能力是管制员能力和工作负荷的重要组成部分。针对此方面缺乏系统研究的实际，详细分析了管制员信息处理能力的影响因素，给出了评价指标体系，建立了多级模糊评价模型，实现了此能力的量化评价。通过对管制员的具体评价，符合管制员的自身情况，证明了方法的有效性。     

Is the need for a new ATM operational concept a strategic necessity?

We must face the fact that conventional methods of air traffic management (ATM) that have served us well cannot continue to cope indefinitely. We need-therefore, to decide what the new operational concept should be and agree on the transition path. Air traffic management is the term we apply today to the totality of the activities involved in the handling of air traffic. The quest for a new concept led to what was first called "free flight," an idea that has, in the meantime, acquired some notoriety and is today more commonly referred to in Europe as "air/ground cooperative ATS." Simply put, the original free flight concept, stipulated that given the right on-board equipment (display of traffic information, conflict detection, and resolution tools) aircraft could navigate and avoid each other completely on their own, without the need for ATC. That a new ATM operational concept will be needed to take the industry further by the time traditional methods run out of potential is difficult to question. Equally clear is that the only new concept available is free flight a.k.a. air/ground cooperative ATS.     

空中交通管制员疲劳检测与管理综述

我国民航事业的发展需要依靠大型运输客机的自主研发和高效的空中交通管理体系两大软硬实力的支撑。空中交通管制员作为空中交通管理的核心要素,其疲劳状态的检测与管理对于航空安全具有重要作用。本文首先从传统主观量表评定和客观评定方法两个方面详细阐述了国内外疲劳检测的研究成果,分析其优缺点;然后介绍了基于语音分析的管制员疲劳特征提取与检测算法,并且着重介绍了基于深度学习模型的语音疲劳状态识别算法;最后阐述了管制员疲劳检测成果对管制运行安全和效率提升的应用前景。研究成果可为从事管制员疲劳检测与管理的研究人员提供参考和借鉴。     

无人机空中对接中的视觉导航方法

无人机空中加油是一种能有效提升巡航里程及续航时长的技术手段,近距相对位置和姿态测量技术是其中需要解决的关键问题之一。针对该问题研究了无人机自主空中对接中的视觉导航方法,完成了近距对接的地面实验。首先,利用移动对接图标和无人机的GPS/INS信息进行无人机的粗略导航,完成会合;再充分利用视觉图标的颜色与形状信息,通过颜色分割选取目标可能区域,在这些区域中进行快速椭圆检测,针对椭圆检测算法存在误检测及边缘不重合的问题,提出了椭圆检测与轮廓检测相结合的方法,能够更准确地描述图标边缘;最后,利用改进的OI算法进行相对位姿的估计,实现近距的精确导航。实验结果表明,无人机在较高速度下的跟踪效果良好,采用的视觉导航方法能够满足空中对接中精度与实时性的要求。