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.     

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。     

反射面的轴向电磁散射及外形优化

本文联合运用几何光学和等效电磁流法,导出了金属反射面轴向散射场和雷达截面(RCS)的简洁表达式,研究了从旋转二次曲面(凹面或凸面)中寻找具有最低RCS值的曲面形状优化方法,给出了一个典型实例的单站RCS立体分布图,以及最低RCS值所对应的波谷曲线和最佳表面参数。     

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。     

雷达与ESM相关算法综述

在比较雷达和ＥＳＭ（ＥｌｅｃｔｒｏｎｉｃＳｕｐｐｏｒｔＭｅａｓｕｒｅｍｅｎｔｓ）这两种传感器特点的基础上，分析了雷达与ＥＳＭ相关的特点，介绍了统计方法、模糊方法和优化方法等五种雷达与ＥＳＨ相关算法，并对这些算法进行了评述。     

航天雷达高度表

介绍几种航天雷达高度表，其中包括弹载雷达高度表、“土星”雷达高度表和“天空实验室”雷达高度表，最后介绍一种卫星雷达高度表的设计方法。     

应答式目标旋转运动对雷达速度测量的影响

携带应答机的飞行目标,若除了沿其某一轨道运动外,还作自旋运动,应答机天线辐射相位空间分布的不均匀性会使应答机转发信号产生附加的相位调制,因而导致多卜勒测量雷达的测量误差。本文分析了对称安装三天线园柱形应答式目标回波的多卜勒频率调制。得出了附加多卜勒频率及其各阶导数的解析式。研究了目标旋转速度、方向角(目标旋转轴线与雷达视线的夹角)和回波谱线宽度的关系,以及对雷达多卜勒测量精度的影响,它对于研究自旋再入体测量问题具有实用价值。文章给出了一个典型的三天线园锥目标模拟旋转试验结果。试验中在不同目标转速下由相参雷达跟踪测量目标回波,同时记录中频信号、多卜勒跟踪回路鉴频器输出等有用信息。对试验数据的分析得出了明确的结论:目标旋转使回波信号的谱线展宽、测速误差增大,谱线宽度与目标转速成正比,同时谱线宽度随目标方向角增大而加宽,方向角为90°时旋转影响最大。理论分析得出了与试验相同的结果。虽然试验是在静态下进行的,但问题的分析对质心运动的目标也同样适用。     

星载合成孔径雷达回波多普勒频率的计算

从星载合成孔径雷达（ＳＡＲ）与目标的相对运动关系出发，以ＳＡＲ发射信号的波长、卫星的轨道参数和目标的位置（地心经纬度）为已知条件，导出了计算目标回小以的多普勒频率的解析公式，这对于星载ＳＡＲ系统的性能 初步设计具有重要作用。