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Deformation monitoring using scanning synthetic aperture radar interferometry.

机译：使用扫描合成孔径雷达干涉仪进行变形监测。

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摘要

This dissertation provides the first demonstration of scanning synthetic aperture radar (ScanSAR) advanced interferometry processing for measuring surface deformation. ScanSAR data are synthesized from ERS-1/2 stripmap SAR images over known deformation in Phoenix, Arizona. The strategy is to construct a burst pattern similar to Envisat ScanSAR data and to create a realistic variable-burst synchronization scenario in which any image pair has at least 50% burst overlap.;The Small Baseline Subsets technique is applied to the synthesized data to demonstrate ScanSAR time series analysis for a scenario generally conducive for interferometry. The same processing approach is employed with the stripmap data to validate the results. The differences in ScanSAR and stripmap velocities have a mean and standard deviation of 0.02+/-0.02 cm/year. 96.3% and 99.1% of the velocity differences are within +/-0.1 cm/year and +/-0.2 cm/year, respectively. The RMS deviations between the ScanSAR and stripmap displacement estimates are 0.40+/-0.30 cm. 68.5% and 94.6% of the differences are within +/-0.5 cm and +/-1.0 cm, respectively.;The Permanent Scatterer (PS) technique also is adapted and applied to the synthesized data to demonstrate the presence of PS in ScanSAR data. The atmospheric and nonlinear motion phase derived from a PS analysis of stripmap data are removed from the ScanSAR interferograms. Even for this idealized scenario, the final PS identification yields fewer ScanSAR PS (10 PS/km 2) than the stripmap PS results (312 PS/km2 or 15.6 PS/km2 at the ScanSAR pixel resolution). Based on the calculated likelihood of finding multiple stripmap PS within a ScanSAR pixel, it is concluded that the ScanSAR single scatterer PS model is flawed.;A model is introduced that considers multiple PS within a ScanSAR pixel. The search for two PS per pixel yields 120 PS/km2. The ScanSAR and stripmap PS velocity differences mean is zero and standard deviation is 0.02 cm/year. However, while the differences between the ScanSAR and stripmap PS DEM error estimates are zero-mean, they have a 7-meter standard deviation. One possible explanation for this relatively large deviation is the differencing of the wrong ScanSAR and stripmap PS as the result of a misalignment between the ScanSAR and stripmap images.
机译：本文首次展示了扫描合成孔径雷达（ScanSAR）先进干涉测量技术用于测量表面变形的过程。 ScanSAR数据是根据ERS-1 / 2条形图SAR图像在亚利桑那州凤凰城发生的已知变形后合成的。该策略是构建类似于Envisat ScanSAR数据的突发模式，并创建一种现实的可变突发同步方案，其中任何图像对都具有至少50％的突发重叠。;将小基线子集技术应用于合成数据以演示针对通常有利于干涉测量的场景的ScanSAR时间序列分析。带状图数据使用相同的处理方法来验证结果。 ScanSAR和带状图速度的差异的平均值和标准偏差为0.02 +/- 0.02 cm /年。 96.3％和99.1％的速度差异分别在+/- 0.1 cm /年和+/- 0.2 cm /年内。 ScanSAR和带状图位移估计之间的RMS偏差为0.40 +/- 0.30 cm。 68.5％和94.6％的差异分别在+/- 0.5 cm和+/- 1.0 cm之内。永久散射体（PS）技术也适用于合成数据，以证明ScanSAR数据中存在PS 。从条形图数据的PS分析得出的大气和非线性运动相位已从ScanSAR干涉图中删除。即使对于这种理想情况，最终的PS标识也比条带图PS结果（312 SAR / km2或在ScanSAR像素分辨率下为15.6 PS / km2）产生的ScanSAR PS（10 PS / km 2）更少。基于计算出的在一个SARSAR像素内找到多个条带状图PS的可能性，得出结论：ScanSAR单散射体PS模型存在缺陷。引入了一种在ScanSAR像素内考虑多个PS的模型。每像素两个PS的搜索产生120 PS / km2。 ScanSAR和stripmap PS速度差平均值为零，标准偏差为0.02 cm /年。但是，尽管ScanSAR和stripmap PS DEM误差估计之间的差为零均值，但它们的标准偏差为7米。对于这种相对较大偏差的一种可能的解释是，由于ScanSAR和条带图图像之间未对齐，导致了错误的ScanSAR和条带图PS的差异。

著录项

  • 作者

    Gudipati, Krishna Vikas.;

  • 作者单位

    The University of Texas at Austin.;

  • 授予单位 The University of Texas at Austin.;
  • 学科 Engineering Aerospace.;Remote Sensing.
  • 学位 Ph.D.
  • 年度 2009
  • 页码 216 p.
  • 总页数 216
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 航空、航天技术的研究与探索;遥感技术;
  • 关键词

  • 入库时间 2022-08-17 11:38:07

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