利用机载GNSS-R的有效波高反演技术

采用自主研发的多源多宿GNSS-R(Global Navigation Satellite System-Reflections,全球导航卫星系统反射信号)海洋环境遥感探测系统,在天津渤海湾特定区域进行了3次机载校飞试验,获得了大量有效GNSS-R信号数据,对自然条件下的海面有效波高进行了反演处理。该系统通过对接收的GNSS直达信号和海面反射信号进行相关运算处理,可以获得DDM(Delay-Doppler Mapping,时延—多普勒映射)图谱,再利用DCF(Derivative of the Correlation Function,相关函数的导数)在DDM图谱基础上进行相关功率波形的计算,进而通过计算DCF的函数波形宽度得到海面有效波高,验证了该方法的可行性。该方法具有全天时、全天候、高分辨率、低成本等优点,对全球范围内中小尺度海洋状态和物理现象的监测具有重要意义。     

白天激光漫反射测距中微弱信号检测的单开门多触发方法

白天激光漫反射测距因存在强背景噪声,导致微弱回波信号的检测十分困难,严重限制了激光漫反射测距的广泛应用。因此,提出了采用单开门多触发方法解决白天激光漫反射测距的微弱信号检测难题。首先,介绍了一种GM-APD (Geiger-ModeAvalanchePhotoDiode,盖革模式雪崩光电二极管)多触发概率分布函数的快速求解方法。接着,取激光漫反射测距系统典型参数,理论分析了多触发情况下的回波信号检测概率,分析结果表明单开门多触发方法可提高激光漫反射测距在白天情况下的回波信号检测概率。同时,通过对触发次数限制的优选,可以增加有效检测比,减少白天观测条件下回波信号的提取代价。最终,通过系统仿真验证了理论分析结果的正确性。因此,单开门多触发方法是解决白天激光漫反射测距微弱信号检测的可行途径之一。     

一种有源高带外抑制导航天线设计

设计了一种有源高带外抑制导航天线,能够有效抑制弹上数据链天线的高功率干扰,适应弹上复杂电磁环境。     

基于地球红外背景模拟的 水云大气影响初步分析

为支持地球红外背景的模拟研究,以天基观测为前提,计算了2个大气窗口下,4个具有典型大气和地表特征的区域在水云大气下的路径透过率和各成分辐射亮度。通过相对变化比例,讨论了地球背景模拟中水云与地表的图像区分以及地域的影响。结果表明,水云对地球背景辐射传输影响显著:云层下方辐射会被强烈衰减,同时观测路径中的散射辐射大幅增强。在同一选定区域下,积云大气的观测路径亮度相对无云大气下变化最大,在相同水云类型条件下,大气散射和太阳散射亮度在不同区域区别较大,说明在模拟水云地球背景时不能忽略地域的影响。计算和分析结果可为地球背景模拟中的水云红外图像生成提供一定的数据基础和技术支持。     

高性能产品(零件)制造技术特征现状的研究分析

系统分析各类高性能制造以注重零件的几何尺寸精度所带来的问题,即在具备超精密、高精度加工能力后,由"合格的高精度零件"装配出的产品至今依然还是合格率低、参数稳定性差的本质内因.首次从零件制造微观角度提出了产品生产合格率低、参数稳定性差是由零件表面微观特征与产品技术特征非匹配性导致的,提出了全新的产品制造理念,从注重零件的几何尺寸精度向关注零件制造微观工艺特征与产品技术特征的匹配性和符合性转变.形成和建立起我国自主创新的高性能产品制造思想和产品制造工艺技术体系,才能从根本上解决产品生产制造合格率低、参数稳定性差等问题,才能形成有继承性、可持续、稳定的产品制造技术体系,而这一切是工业4.0制造模式无法解决的.     

一种新型双线极化BD2 B3抗干扰天线设计

设计了一种双线极化BD2B3抗干扰天线单元,采用2个幅度相等相位相差90°的馈电点,产生幅度相等相位正交的2个线极化波实现双线极化,用该天线单元进行抗干扰阵列组合,能够有效减小天线阵列的体积。     

基于HOG和SVM算法的磨粒图像在线监测技术

为了解决发动机润滑油液磨粒图像监测只适用于微流且易受气泡干扰等问题,设计了一种可适用于相对大流量工作环境的油液磨粒光学图像在线监测系统,区分气泡和磨粒。通过该监测系统,批量采集了一系列磨损颗粒和气泡图片,用于后续图像分类算法的训练与测试。采用了一种基于背景差分和大津法的运动物体提取算法提取出大量磨粒及气泡图像样本,运用基于方向梯度直方图（Histogram of oriented gradients,HOG）进行特征提取和支持向量机（Support vector machine,SVM）分类算法对气泡和磨粒进行识别。实验结果表明,该监测系统能有效采集磨粒及气泡图像并进行自动识别。与基于形态学特征提取算法以及K最近邻（K-nearest neighbor,KNN）等传统分类算法相比,HOG-SVM算法分类精度更高,识别准确率可达83 8%。     

原子钟时域频率稳定性计算方法

首先给出时域频率稳定性分析中各种方差的实用计算公式,并在此基础上分析各种方差特性,总结归纳其适用范围。分析表明：①阿仑方差是时域频率稳定性分析中最常用的方法,但不能区分调相白噪声和调相闪变噪声;②改进阿仑方差通过相位平滑运算能识别这2种噪声;③时间方差和时间总方差主要用于描述频率源的时间波动,主要用于分析调相噪声;④当频率漂移项较大或受甚低频噪声影响时,哈达玛系列方差能给出很好的测量特性。     

Evolution of periodic orbits near the Lagrangian point L2

A study of the evolution of the periodic and the quasi-periodic orbits near the Lagrangian point L₂, which is located to the right of the smaller primary on the line joining the primaries and whose distance from the more massive primary is greater than the distance between the primaries, in the framework of restricted three-body problem for the Sun–Jupiter, Earth–Moon (relatively large mass ratio) and Saturn–Titan (relatively small mass ratio) systems is made. Two families of periodic orbits around the smaller primary are identified using the Poincaré surface of section method – family I (initially elliptical, gradually becomes egg-shaped with the increase in the Jacobi constant C and elongated towards the more massive primary) and family II (initially egg-shaped orbits elongated towards L₂ and gradually becomes elliptical with the increase in C). The family I in the Sun–Jupiter and Saturn–Titan systems contains two separatrix caused by third-order and fourth-order resonances, while the Earth–Moon system has only one separatrix which is caused by third-order resonances. Also in the Sun–Jupiter and the Saturn–Titan systems, family I merge with family II, around Jacobian constant 3.0393 and 3.0163, respectively, while in the Earth–Moon system, family II evolves separately from two different branches. The two branches merge at C = 3.184515. In the Earth–Moon system, the family II contains a separatrix due to third-order resonances which is absent in the other two systems.     

Mining Spatial Associations with Limited Sensory Information

Abstract

Human navigation in an unknown environment requires an understanding of the spatial relationships of the terrain. For example, a soldier who is on a reconnaissance mission in a new city needs to “know” the spatial layout of the surroundings with high confidence. Oftentimes, this understanding must be acquired within a very short amount of time and with limited sensory inputs. The soldier would benefit from a digital avatar that draws inferences about the spatial layout of the city based on an initial set of observations and guides the soldier either in further exploring the environment or in making decisions based on these inferences. In this paper, we present and evaluate an inductive approach to learning spatial associations using sensory data that is available from the simulation environment of a computer game, Unreal Tournament. We study two kinds of spatial relationships between nodes on a level of a game map: nodes that are placed near each other to satisfy some spatial requirement and nodes that are placed near each other to satisfy the design preferences of a level architect. We show that we can infer both kinds of relationships using an association rule mining algorithm. Furthermore, we show how to use an ontology to distinguish between these relationships in order to discover different types of spatial arrangements on a specific map. We discuss how the inferred associations can be used to control an avatar that makes recommendations for navigating unexplored areas on a map. We conclude with some thoughts on the applicability of our methods to scenarios in the real world, beyond the simulation environment of a game, and on how the learned associations can be represented and queried by a simple question-answer type system.