国外机载海面监视雷达发展现状与趋势

首先对目前西方国家装备的较先进的机载海面监视雷达进行了介绍,总结了它们的技术特点。现役机载海面监视雷达具有多功能和多工作模式的特点,除增强了对高海况下的小目标检测能力外,还新增了气象探测、SAR/ISAR和HRRP等先进功能。最后指出了机载海面监视雷达未来发展趋势。     

飞翼无人机结构布局分级优化研究

针对传统结构设计中依据经验对机翼构件布局设计容易导致结构刚度偏大、重量偏大的问题,采用分离设计变量的方法,分别对机翼构件的尺寸和位置变量,采用改进的可行性方向法和Hook-Jeeves方法进行优化,将尺寸非线性优化嵌入到无约束位置优化中,以结构的刚度、位移、扭转和强度为约束条件,对布局进行调整.采用多学科框架软件对整个优化过程进行集成,将机翼结构重量作为目标函数,分级对位置和尺寸优化,充分考虑耦合位置和尺寸变量间的相互影响关系,循环迭代,直至得到结构重量的最优值.采用方法对某型飞翼无人机的机翼结构进行优化,结果合理,具有一定的工程应用价值.     

Temporal variation and asymmetry of sunspot and solar plage types from 1930 to 1936

Using the recently converted to digital format heliophysics catalogues of the Ebro Observatory published in the 1930s, we analyse simultaneously the temporal variation and asymmetry of two different solar structures located at different layers of the solar atmosphere: sunspots and solar plages. In particular, we do the research for all the types of sunspots and plages, including the daily and relative frequencies over the solar cycle. The data were catalogued using the sunspot Cortie classification and a solar plage classification scheme proposed by the Ebro Observatory, which group the phenomena by size and shape. For all types of both sunspots and plages, we observe a decrease in their frequency up to the end of solar cycle 16 and an increase over the beginning of solar cycle 17. Furthermore, we note that small sunspot groups are more likely to happen than bigger groups, although single big spots dominate near the solar minimum. The daily frequency of solar plage occurrences shows that there is not a dominance of compact or scattered solar plages. The North-South occurrence distribution of every type in both sunspots and solar plages shows an asymmetry during the solar cycle: in its declining phase, such asymmetry is directed to the north, while in the beginning of a new cycle is directed to the south.     

Development and testing of a statistical texture model for land cover classification of the Black Sea region with MODIS imagery

A statistical model is proposed for analysis of the texture of land cover types for global and regional land cover classification by using texture features extracted by multiresolution image analysis techniques. It consists of four novel indices representing second-order texture, which are calculated after wavelet decomposition of an image and after texture extraction by a new approach that makes use of a four-pixel texture unit. The model was applied to four satellite images of the Black Sea region, obtained by Terra/MODIS and Aqua/MODIS at different spatial resolution. In single texture classification experiments, we used 15 subimages (50 × 50 pixels) of the selected classes of land covers that are present in the satellite images studied. These subimages were subjected to one-level and two-level decompositions by using orthonormal spline and Gabor-like spline wavelets. The texture indices were calculated and used as feature vectors in the supervised classification system with neural networks. The testing of the model was based on the use of two kinds of widely accepted statistical texture quantities: five texture features determined by the co-occurrence matrix (angular second moment, contrast, correlation, inverse difference moment, entropy), and four statistical texture features determined after the wavelet transformation (mean, standard deviation, energy, entropy). The supervised neural network classification was performed and the discrimination ability of the proposed texture indices was found comparable with that for the sets of five GLCM texture features and four wavelet-based texture features. The results obtained from the neural network classifier showed that the proposed texture model yielded an accuracy of 92.86% on average after orthonormal wavelet decomposition and 100% after Gabor-like wavelet decomposition for texture classification of the examined land cover types on satellite images.     

基于云特征的遥感图像可用度影响因素分析

针对卫星遥感图像可用度分类问题,提出基于图像信息的云覆盖率、云厚度、云破碎度的云结构特征描述概念.研究了它们对于卫星遥感图像可用信息量的影响程度,构建了由厚度相关的云覆盖率及云破碎度构成正交可用度评估空间.并进一步分析了云结构特征与可用度之间的近似线性及单调特点,证实了所提描述方法对于可用度表征的合理性和有效性.通过与500幅不同可用度等级的专业人工判读结果比较,证实综合这3个变量的可用度判读结果与人工判读结果的准确度比较达到95%.该方法为建立卫星遥感图像可用度评估模型,自动分类得到用户需要的图像数据提供理论及技术支持.     

基于共享最近邻的专利自动分类技术研究

专利文献是一种具有法律效力的科技文献,其内容覆盖了几乎所有的技术领域的最新、最活跃的创新技术信息,因此对专利文献的分类和组织在专利管理中有着重要意义。本文通过对现有的专利自动分类技术的归纳和分析,融合BM25相似度计算方法和样本邻域信息提出一种基于共享最近邻的KNN专利自动分类方法。本方法的有效性在NTCIR-8专利分类评测任务中得到充分验证。     

工程图尺寸标注自动布局算法及实现

在由三维模型生成二维工程图的过程中,各主流CAD软件都提供了部分尺寸的自动标注功能,但这些自动生成的尺寸标注放置往往十分杂乱,无法满足尺寸标注的布局要求。针对这一问题,以工程图中大量存在的水平尺寸标注与竖直尺寸标注为研究对象,根据其特点对其进行尺寸子集划分与包容关系排序,在此基础之上,应用增量式尺寸标注自动布局算法,实现水平尺寸标注与竖直尺寸标注的自动布局。算法已在NX平台上得以实现,取得了良好的效果。     

基于最小距离法的遥感图像分类

本文在ENVI遥感图像分析软件环境下,利用最小距离法对遥感图像进行了有监督分类。仿真实验通过对遥感图像中地物目标的光谱信息和空间信息进行分析及特征提取,利用判别函数计算到中心的距离,解读遥感图像,并对分类结果进行定量评估。实验结果表明用最小距离法来分析遥感图像可以获得较高精确度。     

一种新的玫瑰扫描目标跟踪边界重心法

针对自动寻的导弹玫瑰扫描目标跟踪方法中由于扫描过程非线性引起的目标采样非线性,导致求取目标重心算法的运算量和计算误差大等问题,提出了一种基于格林公式的、新的求取目标重心的边界重心法,该方法仅使用目标边界上的采样点。通过对运算量和计算误差的理论分析,与现有的权重重心法相比,本方法可以有效解决采样不均匀的问题,同时运算量减少了90%,误差仅为权重重心法的下界。另外,本方法也可用于基于图像信息的凝视目标跟踪等类似算法中来提高跟踪准确性及运算速度。     

面向大数据的数据处理与分析算法综述

大数据处理是近年来广受关注和研究的技术领域,数据挖掘作为从大量数据中挖掘隐藏价值信息的技术,是处理大数据的有效工具。本文主要从数据挖掘的角度对大数据处理算法的研究现状进行分类总结。首先介绍了大数据中针对流式数据分类的方法,包括单模型算法和集成分类算法;其次分别从单机算法和基于分布式并行平台的多机算法两个角度概括介绍了大数据聚类方法以及大数据关联规则挖掘方法;最后总结了现有面向大数据的数据挖掘算法的研究进展并展望未来的发展趋势。