Manifold structure preservative for hyperspectral target detection

A nonparametric method termed as manifold structure preservative (MSP) is proposed in this paper for hyperspectral target detection. MSP transforms the feature space of data to maximize the separation between target and background signals. Moreover, it minimizes the reconstruction error of targets and preserves the topological structure of data in the projected feature space. MSP does not need to consider any distribution for target and background data. So, it can achieve accurate results in real scenarios due to avoiding unreliable assumptions. The proposed MSP detector is compared to several popular detectors and the experiments on a synthetic data and two real hyperspectral images indicate the superior ability of it in target detection.     

A robust object-based shadow detection method for cloud-free high resolution satellite images over urban areas and water bodies

Unwanted contrast in high resolution satellite images such as shadow areas directly affects the result of further processing in urban remote sensing images. Detecting and finding the precise position of shadows is critical in different remote sensing processing chains such as change detection, image classification and digital elevation model generation from stereo images. The spectral similarity between shadow areas, water bodies, and some dark asphalt roads makes the development of robust shadow detection algorithms challenging. In addition, most of the existing methods work on pixel-level and neglect the contextual information contained in neighboring pixels. In this paper, a new object-based shadow detection framework is introduced. In the proposed method a pixel-level shadow mask is built by extending established thresholding methods with a new C₄ index which enables to solve the ambiguity of shadow and water bodies. Then the pixel-based results are further processed in an object-based majority analysis to detect the final shadow objects. Four different high resolution satellite images are used to validate this new approach. The result shows the superiority of the proposed method over some state-of-the-art shadow detection method with an average of 96% in F-measure.     

历经十年寿命试验的消旋天线机构轴承的可靠性分析

解决了一个计算可靠性问题的特例。分析了消旋天线机构轴承历经10年寿命试验的可靠性问题。并给出了轴承在不同可靠寿命要求下的可靠度(对应不同置信度)。     

波导分支线定向耦合器计算方法

利用模匹配方法和网络理论分析计算了一种卫星天线系统中常用的波导分支线定向耦合器,计算结果与实验结果非常吻合。该方法为波导分支线定向耦合器提供一种有力的设计手段。它可直接用于设计Ku 波段通信卫星天线的波束形成网络,也可以用来设计各种耦合度的波导分支线定向耦合器。     

故障检测与分离的广义一致性算子法

本文提出了故障检测与分离的广义一致性算子法的一般形式。得出了两个故障可分离的充要条件和多个故障可分离的充要条件。最后给出了检测和分离故障的过程。     

利用偏馈振子调整测控雷达跟踪通道相移技术研究

提出一种调整雷达跟踪通道相移的方法 ,即在雷达天线主面上配置偏馈振子 ,利用偏馈振子做为校准源调整雷达跟踪和 /差通道间的相移 ,并对该方法的可行性、可靠性及稳定性进行了实验研究。     

神经网络在未来超分辨雷达中的应用

最新的技术发展已为研制超分辨雷达创造了条件。它能够突破普通雷达基于匹配滤波原理的分辨能力,而实现超分辨。超分辨雷达的巨大计算量通常来自求解非线性最小二乘问题时的多维搜索。本文针对这一问题,研究了雷达信号处理中的两个典型例子:(1)利用阵列处理检测个数已知而方向未知的雷达目标;(2)对波音727飞机进行超分辨距离多普勒成像。说明Hop-field神经网络通过集体运算能够求解各种困难的最优化问题,因而在未来的超分辨雷达中有广阔的应用前景。     

一种适于动态环境的盲多用户检测算法

比较两种盲多用户检测算法在动态环境中的收敛性能,并通过计算机进行模拟仿真。其中一种是能随输入信号矢量变化而变化的变步长最小输出能量盲算法;另一种是既保持最小输出能量检测器的全局收敛性,又具有最小均方误差检测器高输出信干比优点的判决反馈变步长盲算法。利用前者在动态强干扰下收敛快及后者在稳态时输出信干比高的优势,将二者结合起来应用到动态环境中,提高系统性能,同时抑制多址干扰和窄带干扰。     

引信天线参数设计中的概率方法

本文从引信的最一般概念出发给出了确定引信天线付瓣电平参数的概率解析法，论理严谨，经济适用，根据这种方法确定天线付瓣电平是建立在引信付瓣启动的小概率原理上的。适用于小型计算机计算。文中还给出了计算实例供设计参考。     

导引头天线的研究方向

在简要介绍雷达导引头天线发展概况的基础上，论述了新一代雷达导引头天线的体制、形式及结构特点，提出导引头天线的技术发展方向是高效率、低旁瓣、薄型化。最后指出，毫米波导引头天线也是今后导头天线的研究方向。