基于DOA聚类算法的ARM抗有源诱偏技术研究

有源诱偏技术是雷达对抗反辐射导弹的一种重要手段,可以大大降低反辐射导弹的作战效能。为提高对敌目标的精确打击能力,在分析闪烁诱饵诱偏原理的基础上,针对有源诱偏干扰下被动雷达测角精度与稳定度不高的问题,通过对有源诱偏信号的时域特征进行分析,提出一种基于脉冲前沿检测的DOA聚类分选算法,找出前沿超前的辐射源信号,实现了高性能抗有源诱偏干扰和高精度抗干扰测向。仿真结果表明,该技术可以有效对抗四点源有源诱偏干扰。     

航天嵌入式软件数组越界缺陷特征研究

根据统计,数组越界是航天嵌入式软件开发过程中出现最多且最容易被遗漏的缺陷类型之一.目前自动化检测数组越界多基于抽象解释、符号执行、程序模型检验等方法,这些方法在误报、漏报、可扩展性等方面的表现依赖于软件及缺陷特征.分析了近三年航天嵌入式软件第三方测试中发现的94个数组越界问题,从缺陷模式和缺陷表现形式两方面分析得出10项航天嵌入式软件数组越界缺陷特征,并提出对设计具体检测方法关键的若干启示.进一步基于这些特征和启示探讨了数组越界检测算法针对中断驱动型程序的改进方向.     

Multi-scale design and optimization for solid-lattice hybrid structures and their application to aerospace vehicle components

By integrating topology optimization and lattice-based optimization, a novel multi-scale design method is proposed to create solid-lattice hybrid structures and thus to improve the mechanical performance as well as reduce the structural weight. To achieve this purpose, a two-step procedure is developed to design and optimize the innovative structures. Initially, the classical topology optimization is utilized to find the optimal material layout and primary load carrying paths. Afterwards, the solid-lattice hybrid structures are reconstructed using the finite element mesh based modeling method. And lattice-based optimization is performed to obtain the optimal cross-section area of the lattice structures. Finally, two typical aerospace structures are optimized to demonstrate the effectiveness of the proposed optimization framework. The numerical results are quite encouraging since the solid-lattice hybrid structures obtained by the presented approach show remarkably improved performance when compared with traditional designs.     

一种基于OPTICS聚类的仅测角导航目标检测算法

仅测角自主导航方法具有设备简单、复杂度低，功耗低的优点，在空间任务中具有广泛的应用前景.针对中远距离下空间目标特征少的特点，提出了一种利用基于OPTICS聚类算法的空间目标检测方法，可用于仅测角导航过程中的目标检测.对原始星图进行预处理提取星点及目标点，并结合星图识别的结果选择部分帧，使用经过改进的OPTICS聚类方法获得目标运动轨迹.最后，使用本文中的算法对软件仿真出的含有目标的高精度星图进行处理验证了算法的可行性.在卫星相对于空间目标抵近过程中，目标检测的水平误差及垂直误差小于0.15°的帧数分别占到了85.4%以及99.6%.相比AVANTI实验中的目标检测方法，减少了在轨任务中相关参数的调节，进一步提升了算法的自主性.     

微纳聚合体卫星的对称式重构规划算法

为解决微纳聚合体卫星变构过程中，聚合体各部分之间的动力学耦合导致的卫星整体姿态翻转或紊乱，提出了一种对称式变构规划算法。首先建立了铰链约束下的漂浮基多刚体系统动力学模型，研究了重构过程中各运动模块对本体姿态的影响，提出当每两个运动模块位置与转动方向满足对称性条件时，两者对本体姿态的影响可在一定程度上相互抵消。基于上述理论，在A*算法中引入最优分配度量和对称性判定，设计了并行对称重构规划算法。仿真结果表明，该规划算法可实现重构过程中多模块并行、对称运动，重构过程总步数较少，运动模块对本体姿态的影响小。     

短螺旋型燃烧室旋流结构及气动边界发展规律数值模拟研究

短螺旋型燃烧室的头部轴线沿发动机周向与发动机轴线偏转一定角度,可以在保证燃烧效率不变的条件下有效缩短燃烧室轴向长度。短螺旋型燃烧室流场的最大特点是旋流流动单侧受限。为了研究头部安装角α变化对燃烧室旋流流动特性的影响,基于数值方法对短螺旋型燃烧室进行了计算分析。结果表明:随着α变化,旋流器下游旋涡依次出现对称环状、马蹄状、环状结构;随着α增加,气动边界逐渐出现并抑制旋流的周向扩张,导致流场出现不同的旋涡结构;不同α下的切向角动量随轴向距离增加而衰减,但α为35°和45°时,气动边界在非受限侧出现并对旋流产生约束,角动量衰减变慢;当α为0°,15°,35°,45°时,燃油液滴依次集中分布在旋流器下游两旋涡边缘、侧壁面和头部端壁、非受限旋涡边缘。本文研究了不同α下的旋涡结构及气动边界沿轴向的演化过程,为短螺旋型燃烧室进一步的设计与优化提供基础。     

A comprehensive survey on the methods of angle of attack measurement and estimation in UAVs

Angle of Attack (AOA) is a crucial parameter which directly affects the aerodynamic forces of an aircraft. The measurement of AOA is required to ensure a safe flight within its designed flight envelop. This paper intends to summarise a comprehensive survey on the measurement techniques and estimation methods for AOA, specifically in Unmanned Aerial Vehicle (UAV) applications. In the case of UAVs, weight constraint plays a major role as far as sensor suites are concerned. This results in selecting a suitable estimation method to extract AOA using the available data from the autopilot. The most feasible and widely employed AOA measurement technique is by using the Multi-Hole Probes (MHPs). The MHP measures the AOA regarding the pressure variations between the ports. Due to the importance of MHP in AOA measurement, the calibration methods for the MHP are also included in this paper. This paper discusses the AOA measurement using virtual AOA sensors, their importance and the operation.     

Which way is the bookstore? A closer look at the judgments of relative directions task

We present a detailed analysis of a widely used assay in human spatial cognition, the judgments of relative direction (JRD) task. We conducted three experiments involving virtual navigation interspersed with the JRD task, and included confidence judgments and map drawing as additional metrics. We also present a technique for assessing the similarity of the cognitive representations underlying performance on the JRD and map-drawing tasks. Our results support the construct validity of the JRD task and its connection to allocentric representation. Additionally, we found that chance performance on the JRD task depends on the distribution of the angles of participants’ responses, rather than being constant and 90 degrees. Accordingly, we present a method for better determining chance performance.     

超临界CO2技术对空心/实心石英混编纤维表面改性

采用热处理+溶剂浸洗+超临界CO2技术对空心/实心石英混编纤维表面进行预处理,同时利用超临界流体的携带与渗透作用,将KH-560偶联剂引入纤维表面进行改性。采用接触角测试、表/界面张力测试、树脂吸附量测试、力学性能测试、扫描电镜等分别测试纤维表面能、胶液表面张力与接触角、胶液与纤维浸润性,观察纤维表面形貌结构,分析复合材料的力学与介电性能。结果表明:采用热处理+溶剂浸洗+超临界CO2技术可有效去除空心/实心石英混编纤维表面浸润剂,提高纤维表面能,促进胶液与纤维的完全浸润,最终改善复合材料力学与介电性能。     

基于函数链神经网络的深度分类器

目前的宽度学习系统（Broad learning system，BLS）通过所建立的一系列映射节点和增强节点来形成联合节点。因为联合节点与输出层的线性连接，网络权值可以用求解伪逆的方法快速求得，避免了耗时的训练过程，从而成为快速而高效的学习方法。然而在追求高精度结果的过程中，BLS对于增强节点数量的需求过于巨大，容易造成过拟合问题。为此，本文提出了基于函数链神经网络（Functional-link neural network，FLNN）的深度分类器（FLNN based deep classifier，FLNNDC），旨在提供一种更加简单却又不失精度的BLS变体结构。FLNNDC将几个轻量级的BLS子系统堆积成栈式结构，每一个轻量级的BLS子系统随机选择一部分映射节点生成增强节点，而不是全部映射节点。和原宽度结构相比，在几个主流数据集上的实验结果表明本文所提出的FLNNDC分类器具有网络结构更小且学习速度更快的优势。