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.     

Measuring the matter distribution within z = 0.2 cluster lenses with XMM-Newton

We present an analysis of seven clusters observed by XMM-Newton as part of our survey of 17 most X-ray luminous clusters of galaxies at z  0.2 selected for a comprehensive and unbiased study of the mass distribution in massive clusters. Using the public software FTOOLS and XMMSAS we have set up an automated pipeline to reduce the EPIC MOS and pn spectro-imaging data, optimized for extended sources analysis. We also developped a code to perform intensive spectral and imaging analysis particularly focussing on proper background estimate and removal. XMM-Newton deep spectro-imaging of these clusters allowed us to fit a standard β-model to their gas emission profiles as well as a standard MEKAL emission model to their extracted spectra, and test their inferred characteristics against already calibrated relations.     

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。     

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。     

N2O-C2H2火焰原子吸收光谱法测定纯镍中硅含量

为简化纯镍中硅含量的测定过程,提高测量精度,研究了一种N2O-C2H2火焰原子吸收光谱法用于检测。介绍了方法的原理、工作参数和测定条件,并确定最佳工作条件,讨论了燃烧温度、共存离子等干扰因素的影响。实验结果表明,该法的灵敏度高、干扰小、选择性和重现性好,操作简单,分析周期短。其测定结果的相对标准偏差均小于1.0%,标准加入回收率大于97.0%(样本数n=6),可满足实验室仪器分析质量与控制的要求。     

画幅式层析成像光谱系统设计和实验研究

文章介绍一种无需时间或空间扫描的新型成像光谱仪—利用位相光栅作为分束器件的计算层析成像光谱仪 (CTIS)。重点介绍了各个系统的设计原则和位相光栅的设计 ,并给出了光栅的设计结果。详细介绍系统矩阵的实验定标方法和过程。叙述了自然光照明条件下真实物体组成的靶标的光谱成像实验 ,对目标实验采样的数据进行重构处理 ,给出了实验结果。     

几种新型的星载多光谱和成像光谱仪

近几年出现了几种新型的星载多光谱和成像光谱仪,例如:Landsat-7卫星的有效载荷增强型主题测绘仪+（ETM+）;EOS AM-1卫星的有效载荷多角度成像光谱仪（MISR）和先进空间热发射和反射辐射计（ASTER）;特殊探测器紫外成像光谱仪（SSUSI）。文章从结构、性能参数等方面综述了这几种星载成像光谱仪。     

成像光谱仪编程选择波段数据采集系统的研究

随着成像光谱仪的发展,遥感数据量越来越大,这对电子学系统中的数据采集、传输和处理带来了一定的困难。基于目前技术和数据的实用性两方面考虑,采用编程选择波段的方法能够很好地解决数据量日益增大的问题,国内外的一些方案中已经对此有了一定的设想,即通过遥控指令改变波段数目、光谱取样间隔或波段的重组,这一切都要求有一个灵活性强、通用性好的数据采集系统,能够对不同的选择情况正确地收集用户所需的数据。文中对数据采集的可行性进行了研究,并提出了一个较为容易实现的方案。