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Extending interferometric synthetic aperture radar measurements from one to two dimensions.

机译:将干涉式合成孔径雷达测量范围从一维扩展到二维。

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摘要

Interferometric synthetic aperture radar (InSAR), a very effective technique for measuring crustal deformation, provides measurements in only one dimension, along the radar line of sight. Imaging radar measurements from satellite-based systems are sensitive to both vertical and across-track displacements, but insensitive to along-track displacement. Multiple observations can resolve the first two components, but the along-track component remains elusive. The best existing method to obtain the along-track displacement involves pixel-level azimuth cross-correlation. The measurements are quite coarse (typically 15 cm precision), and they require large computation times. In contrast, across-track and vertical InSAR measurements can reach centimeter-level precision and are readily derived.; We present a new method to extract along-track displacements from InSAR data. The new method, multiple aperture InSAR (MAI), is based on split-beam processing of InSAR data to create forward- and backward-looking interferograms. The phase difference between the two modified interferograms provides the along-track displacement component. Thus, from each conventional InSAR pair we extract two components of the displacement vector: one along the line of sight, the other in the along-track direction. Multiple MAI observations, either at two look angles or from the ascending and descending radar passes, then yield the three-dimensional displacement field.; We analyze precision of our method by comparing our solution to GPS and offset-derived along-track displacements from interferograms of the M7.1 1999, Hector Mine earthquake. The RMS error between GPS displacements and our results ranges from 5 to 8.8cm. Our method is consistent with along-track displacements derived by pixel-offsets, themselves limited to 12-15cm precision. The theoretical MAI precision depends on SNR and coherence. For SNR=100 the expected precision is 3, 11cm for coherence of 0.8, 0.4, respectively.; Finally, we evaluate how the new measurements improve the determination of the earthquake coseismic slip distribution by comparison of models derived from multiple data types. We find that MAI data help constrain the southern portion of the lip distribution, by adding information where GPS data are sparse and the deformation is below the azimuth pixel-offsets detection threshold.
机译:干涉式合成孔径雷达(InSAR)是一种非常有效的测量地壳变形的技术,它只能沿雷达视线在一个维度上进行测量。来自卫星系统的成像雷达测量对垂直和跨轨道位移都敏感,但对沿轨道的位移不敏感。多个观测值可以解析前两个分量,但沿轨分量仍然难以捉摸。获得沿轨位移的最佳现有方法涉及像素级方位角互相关。测量值相当粗略(通常为15 cm精度),并且它们需要大量的计算时间。相反,跨轨和垂直InSAR测量可以达到厘米级的精度,并且很容易得出。我们提出了一种从InSAR数据中提取沿轨位移的新方法。新方法,多孔径InSAR(MAI),是基于InSAR数据的分割光束处理,以创建前视和后视干涉图。两个修改后的干涉图之间的相位差提供了沿轨迹的位移分量。因此,我们从每个常规InSAR对中提取位移矢量的两个分量:一个沿视线,另一个沿沿轨道方向。多次MAI观测,无论是从两个视角还是从雷达波的上升和下降,都将产生三维位移场。通过比较我们对GPS的解决方案和从赫克托矿1999年M7.1地震的干涉图得出的偏移量沿轨迹位移的方法,我们分析了方法的精度。 GPS位移与结果之间的RMS误差范围为5到8.8cm。我们的方法与由像素偏移量得出的沿轨迹的位移一致,而像素偏移量自身的精度限制为12-15cm。 MAI的理论精度取决于SNR和相干性。对于SNR = 100,相干度为0.8、0.4时,预期精度分别为3、11cm。最后,通过比较从多种数据类型得出的模型,我们评估了新的测量结果如何改善对地震同震滑动分布的确定。我们发现,通过添加GPS数据稀疏且变形低于方位角像素偏移检测阈值的信息,MAI数据有助于约束嘴唇分布的南部。

著录项

  • 作者

    Bechor, Noah.;

  • 作者单位

    Stanford University.;

  • 授予单位 Stanford University.;
  • 学科 Geodesy.; Geophysics.
  • 学位 Ph.D.
  • 年度 2007
  • 页码 62 p.
  • 总页数 62
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 大地测量学;地球物理学;
  • 关键词

  • 入库时间 2022-08-17 11:39:46

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