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Detection of target scattering centers in terrain clutter using an ultra-wideband, fully polarimetric synthetic aperture radar.

机译:使用超宽带全极化合成孔径雷达检测地形杂波中的目标散射中心。

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摘要

In this dissertation, we study the processing of full-polarization data collected by an ultra-wideband synthetic aperture radar in order to detect targets embedded in terrain clutter. We focus on the use of polarization diversity in a high resolution application to incorporate partial knowledge of the target into the detector design and to model geometrically relevant unknown parameters.; We consider a family of generalized likelihood ratio (GLR) detectors that assume varying degrees of knowledge about the target. The detectors are based on a deterministic model of target scattering that is parameterized in terms of the geometrically relevant Huynen scattering parameters. The GLR detectors form maximum likelihood (ML) estimates of the unknown target scattering parameters. These estimates may be used to further describe a detected target for the purpose of identification. We restrict ourselves to single-pixel-based detectors of canonical scattering centers that comprise the response of a distributed target. This approach may be extended to multi-pixel tests in order to compress distributed target response energy.; One member of the GLR family is a new detector that assumes unknown target amplitude, phase, and orientation about the radar line of sight. These three parameters are unknown in many practical applications. The performance of the new detector is found to lie between that of the well-known OPD and PWF polarimetric detectors.; Detector performance in a real application depends on the accuracy of the assumed clutter statistical model. We analyze the statistics of real forest clutter at low frequencies in order to choose a realistic clutter model. We find that the K-distribution is better suited to modeling the "heavy-tail" distribution of the clutter than the Gaussian distribution.; We implement and analyze the performance of GLR detectors that assume either Gaussian or K-distributed clutter with known covariance. Detector performance is characterized as a function of scattering center orientation angle, false alarm probability, signal-to-noise ratio, and shape parameter of the K-distribution. In addition, we study the statistical mismatch case in which a detector designed for Gaussian clutter is applied to measurements whose clutter component is K-distributed.
机译:本文研究了一种超宽带合成孔径雷达采集的全极化数据的处理过程,以检测地形杂波中嵌入的目标。我们专注于在高分辨率应用中极化分集的使用,以将目标的部分知识整合到探测器设计中,并对几何相关的未知参数进行建模。我们考虑一类广义似然比(GLR)检测器,这些检测器假设对目标的了解程度不同。探测器基于目标散射的确定性模型,该模型根据几何相关的惠恩散射参数进行参数化。 GLR检测器形成未知目标散射参数的最大似然(ML)估计。这些估计可以用于进一步描述用于识别的检测目标。我们将自己限制为包含分散目标响应的规范散射中心的基于单像素的检测器。该方法可以扩展到多像素测试,以便压缩分布的目标响应能量。 GLR系列的成员之一是一种新的探测器,该探测器假定未知的目标幅度,相位和绕雷达视线的方向。这三个参数在许多实际应用中是未知的。发现新检测器的性能介于众所周知的OPD和PWF偏振检测器之间。实际应用中的检测器性能取决于假定的杂波统计模型的准确性。为了选择一个现实的杂波模型,我们分析了低频下真实森林杂波的统计数据。我们发现,K分布比高斯分布更适合于对杂波的“重尾”分布进行建模。我们实现并分析了假设具有高协方差的高斯或K分布杂波的GLR检测器的性能。检测器性能的特征是散射中心定向角,虚警概率,信噪比和K分布的形状参数的函数。此外,我们研究了统计不匹配的情况,其中针对高斯杂波设计的检测器应用于杂波成分为K分布的测量。

著录项

  • 作者

    Dilsavor, Ronald Louis.;

  • 作者单位

    The Ohio State University.;

  • 授予单位 The Ohio State University.;
  • 学科 Engineering Electronics and Electrical.; Remote Sensing.
  • 学位 Ph.D.
  • 年度 1993
  • 页码 193 p.
  • 总页数 193
  • 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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