面向空间应用的GaN功率器件及其辐射效应

研究氮化镓(GaN)功率器件及其辐射效应对于解决空间应用需求、促进新一代航天器建设具有重大意义。介绍了GaN功率器件的主要结构及工作原理,综述了近年来国内外在GaN功率器件的总剂量效应和单粒子效应两方面的研究进展,并对辐射效应在GaN功率器件中造成的退化和损伤机制进行分析与讨论。研究结果显示：GaN功率器件具有较强的抗总剂量能力,但是抗单粒子能力较弱,易发生漏电和单粒子烧毁,且烧毁点多发生在栅极边缘的漏侧。对GaN功率器件辐照损伤机理的研究缺乏权威理论,有待进一步探索,为其空间应用提供理论支撑。目前,平面结构的GaN功率器件是主流的技术方案,单片集成及高频小型化是GaN功率器件未来发展的方向。     

重力扰动对SINS水平姿态的影响

为研究动基座下捷联惯导系统(Strapdown Inertial Navigation System, SINS)水平姿态误差角与水平重力扰动间的关系,推导了南北方向、东西方向匀速直线运动时,SINS纯惯性解算的水平姿态误差与水平重力扰动间的传递函数,并分析了传递函数的零极点分布;推导了组合导航模式下,水平姿态误差角与水平重力扰动间的传递函数;通过仿真分析了纯惯性解算和组合导航模式下传递函数的幅频特性。组合导航相对于纯惯性解算模式,截止频率更大,SINS姿态误差角受更多高频重力扰动信号的影响,因此,组合导航模式需要更高分辨率的重力扰动数据来进行重力扰动补偿。此外,在对高精度SINS进行重力扰动补偿时,对于重力扰动分辨率的需求是有限度的,过于精细的重力扰动数据只会带来测量和存储压力,不能提高SINS的姿态精度。     

太空目标监视装备作战试验设计研究

按照现行装备试验鉴定体制的要求,装备作战试验是新研太空目标监视装备在正式交付使用单位前必须完成的一类试验。太空目标监视装备具有精密昂贵、价值高、单台套、集成度和复杂度高等特点,开展作战试验与普通的侦察探测装备和常规兵器区别较大。本文介绍了太空目标监视装备作战试验的对象与要求,分解了太空目标搜索发现、监视管理、目标识别、信息共享等实战能力和实战能力的生成与保持要求,构建了作战试验评估指标体系,并依据太空目标监视任务剖面和环境剖面设计了作战试验项目,基于作战试验指标考核评估确定了评估数据采集需求,紧贴太空目标监视装备实际使用面临的环境条件构设了逼真的作战试验环境条件。这些研究可为太空目标监视装备作战试验实践提供支持。     

欧盟太空安全政策与发展动向

欧盟具有相对成熟的太空技术,处于国际太空力量发展的第一梯队,其太空安全政策是在基于维护太空自主权的前提下,寻求太空与安全防务政策的统一,从而实现共同外交和安全政策的整体目标,目前已取得了较大进展。本文认为,从未来发展来看,面对有限的太空资源优势和脆弱的太空环境,欧盟将会继续利用其技术优势和集体力量,努力保障其太空关键基础设施安全和太空自主权,同时进一步将太空安全重点向军事竞争领域聚焦,将其作为拓展战场空间维度的重要途径。     

俄罗斯太空安全政策探析

后苏联时代的俄罗斯未能维持其在太空安全领域的优势,已不再是太空军事强国。本文首先梳理了俄罗斯太空安全政策的发展历程,其次,讨论了俄罗斯在太空安全治理和防止太空武器化方面的外交倡议,最后总结了俄罗斯太空安全政策的特征。本研究认为,自21世纪初起,俄罗斯逐渐开始复兴其太空军事力量,力图使其太空安全政策适应新的地缘政治格局,不仅积极调整其航天计划,对其航天工业体系、航天机构和航天资产进行简化、整合和现代化建设,还谋求“非对称”反制策略,并在联合国框架内积极开展“太空外交倡议”,以应对美国太空武器化所带来的威胁和挑战,同时推动禁止太空武器化进程。     

美军太空信息支援战区作战研究

为了保证太空信息能自顶向下融入到战区联合作战行动,实现太空信息支援力量与其他作战部队的跨域协同,美军建立了体系健全、功能完备的太空信息支援系统。本文梳理归纳了美军太空信息支援力量体系,针对太空信息支援战区作战的指挥与运用流程,分析了“统分结合、视情授权”的太空信息支援战区作战指挥体系,研究了“需求提出－汇总分析－分类提供”的支援作战流程,对天基侦察监视、卫星通信中继、卫星导航定位的需求管理、任务规划与资源调度的具体运用流程进行了分析,总结了美军太空信息支援战区作战指挥控制的特点。希冀本研究可为太空信息支援作战的指挥体系构建和指挥控制流程设计提供一定参考。     

Reaction degree of composition B explosive with multi-layered compound structure protection subjected to detonation loading

The explosive reaction degree and protection from explosions are concerns in the military field.In this work,the reaction degree of the composition B explosive was investigated experimentally.Multi-layered compound structures were used as barriers to weaken the blast loads.A comprehensive experiment using a high-speed camera and image processing techniques,side witness plates,and bottom witness plates was presented.Using the experimental fragment velocities,fragment piercing patterns,and damage characteristics,the reaction degree of the explosive impeded by different multi-layered com-pound structures could be precisely differentiated.Reaction parameters of the explosive obstructed by compound structures were obtained by theoretical analysis and numerical simulations.Unlike the common method in which the explosive reaction degree is only distinguished based on the initial pressure amplitude transmitted into the explosive,a following shock wave reflected from the side steel casing was also considered.Different detonation growth paths in the explosive formed.Therefore,all these shock wave propagation characteristics must be considered to analyze the explosive response impeded by compound structures.     

Multi-scale traffic vehicle detection based on faster R-CNN with NAS optimization and feature enrichment

It well known that vehicle detection is an important component of the field of object detection. However, the environment of vehicle detection is particularly sophisticated in practical processes. It is compara-tively difficult to detect vehicles of various scales in traffic scene images, because the vehicles partially obscured by green belts, roadblocks or other vehicles, as well as influence of some low illumination weather. In this paper, we present a model based on Faster R-CNN with NAS optimization and feature enrichment to realize the effective detection of multi-scale vehicle targets in traffic scenes. First, we proposed a Retinex-based image adaptive correction algorithm (RIAC) to enhance the traffic images in the dataset to reduce the influence of shadow and illumination, and improve the image quality. Second, in order to improve the feature expression of the backbone network, we conducted Neural Architecture Search (NAS) on the backbone network used for feature extraction of Faster R-CNN to generate the optimal cross-layer connection to extract multi-layer features more effectively. Third, we used the object Feature Enrichment that combines the multi-layer feature information and the context information of the last layer after cross-layer connection to enrich the information of vehicle targets, and improve the robustness of the model for challenging targets such as small scale and severe occlusion. In the imple-mentation of the model, K-means clustering algorithm was used to select the suitable anchor size for our dataset to improve the convergence speed of the model. Our model has been trained and tested on the UN-DETRAC dataset, and the obtained results indicate that our method has art-of-state detection performance.     

基于系统动力学的导弹体系作战效能仿真研究

简要介绍了系统动力学的概念;分析了导弹作战体系的构成以及各子系统对体系的贡献效能;针对导弹体系对抗作战效能仿真,运用系统动力学方法,建立了导弹体系对抗的系统动力学模型;并对在不同对策条件下的仿真结果进行了分析,为导弹体系结构优化、体系能力的提高提供了依据。     

基于虚拟样机技术的轴对称推力矢量控制伺服机构设计

利用ADAMS软件建立了轴对称推力矢量控制伺服机构的虚拟样机,分析了4个关键设计点对伺服作动器运动时的交连干扰、正负摆角的不对称性以及驱动力臂波动的影响,完成了伺服机构布局方案的优化,为伺服机构布局方案的设计提供了精确的分析模型。