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Focus of attention for millimeter and ultra wideband synthetic aperture radar imagery.

机译:毫米和超宽带合成孔径雷达图像的关注焦点。

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摘要

The major goal of this research is to develop efficient detectors for Synthetic Aperture Radar (SAR) images, exploiting the reflectivity characteristics of targets in different radar types. Target detection is a signal processing problem whereby one attempts to detect a stationary target embedded in background clutter while minimizing the false alarm probability. In radar signal processing, the better resolution provided by the Millimeter Wave (MMW) SAR enhances the detectability of small targets. As radar technology evolves, the newly developed Ultra Wideband (UWB) SAR provides better penetration capabilities to locate concealed targets in foliage.; In this thesis we demonstrate that local intensity kernel tests can be formulated based on the generalized likelihood ratio test (GLRT), while preserving constant false alarm rate (CFAR) characteristics. Both the widely used two-parameter CFAR and the g -CFAR can be viewed as special cases of the local intensity tests with different intensity kernels. It is demonstrated that the first-order Gamma kernel is a good approximation for the principal eigenvector of the projected radial intensity of targets, which provides the optimal matching intensity kernel. This also explains the better performance of the g -CFAR detector over the two parameter CFAR detector.; We also developed different CFAR subspace detectors for UWB images, utilizing a Laguerre function subspace. The driven response produced by natural clutter degrades the performance of these subspace detectors. In addition to the driven response, the distinguishing feature of metallic targets in UWB is the resonance response. Therefore, we further propose a two-stage detection scheme: g -CFAR detector followed by the quadratic Laguerre discriminator (QLD). We evaluate every detector and discriminator using ROC curves in a large area (about 2 km2) of imagery. The combined g -CFAR and quadratic Laguerre discriminator improve the simple Laguerre subspace detector more than one hundred fold for a perfect detection rate (Pd = 1).
机译:这项研究的主要目标是开发合成孔径雷达(SAR)图像的高效探测器,并利用不同雷达类型中目标的反射率特性。目标检测是一种信号处理问题,由此人们试图检测嵌入在背景杂波中的静止目标,同时将误报概率降到最低。在雷达信号处理中,毫米波(MMW)SAR提供的更好分辨率提高了小目标的可检测性。随着雷达技术的发展,新开发的超宽带(UWB)SAR提供了更好的穿透能力,可以定位树叶中的隐蔽目标。在本文中,我们证明了可以基于广义似然比检验(GLRT)制定局部强度核检验,同时保留恒定的误报率(CFAR)特征。广泛使用的两参数CFAR和 g -CFAR都可以看作是使用不同强度核进行局部强度测试的特殊情况。结果表明,一阶伽玛核是对目标投影径向强度的本征向量的良好近似,从而提供了最佳的匹配强度核。这也解释了 g -CFAR检测器优于两个参数CFAR检测器的性能。我们还利用Laguerre函数子空间为UWB图像开发了不同的CFAR子空间检测器。自然杂波产生的驱动响应会降低这些子空间检测器的性能。除了驱动响应之外,UWB中金属靶材的显着特征是谐振响应。因此,我们进一步提出了一个两阶段的检测方案: g -CFAR检测器,然后是二次Laguerre鉴别器(QLD)。我们使用ROC曲线在大面积图像(大约2 km 2 )中评估每个检测器和鉴别器。 g -CFAR和二次Laguerre鉴别器的组合将简单Laguerre子空间检测器提高了100倍以上,从而获得了理想的检测率( P d = 1)。

著录项

  • 作者

    Yen, Li-Kang.;

  • 作者单位

    University of Florida.;

  • 授予单位 University of Florida.;
  • 学科 Engineering Electronics and Electrical.; Remote Sensing.
  • 学位 Ph.D.
  • 年度 1998
  • 页码 139 p.
  • 总页数 139
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 无线电电子学、电信技术;遥感技术;
  • 关键词

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