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Ionospheric Correction of Interferometric SAR Data with Application to the Cryospheric Sciences

机译：干涉SAR数据的电离层校正及其在冰冻圈科学中的应用

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摘要

The ionosphere has been identified as an important error source for spaceborne Synthetic Aperture Radar (SAR) data and SAR Interferometry (InSAR), especially for low frequency SAR missions, operating, e.g., at L-band or P-band. Developing effective algorithms for the correction of ionospheric effects is still a developing and active topic of remote sensing research. The focus of this thesis is to develop robust and accurate techniques for ionospheric correction of SAR and InSAR data and evaluate the benefit of these techniques for cryospheric research fields such as glacier ice velocity tracking and permafrost deformation monitoring. As both topics are mostly concerned with high latitude areas where the ionosphere is often active and characterized by turbulence, ionospheric correction is particularly relevant for these applications.;After an introduction to the research topic in Chapter 1, Chapter 2 will discuss open issues in ionospheric correction including processing issues related to baseline-induced spectrum shifts. The effect of large baseline on split spectrum InSAR technique has been thoroughly evaluated and effective solutions for compensating this effect are proposed. In addition, a multiple sub-band approach is proposed for increasing the algorithm robustness and accuracy. Selected case studies are shown with the purpose of demonstrating the performance of the developed algorithm.;In Chapter 3, the developed ionospheric correction technology is applied to optimize InSAR-based ice velocity measurements over the big ice sheets in Greenland and the Antarctic. Selected case studies are presented to demonstrate and validate the effectiveness of the proposed correction algorithms for ice velocity applications. It is shown that the ionosphere signal can be larger than the actual glacier motion signal in the interior of Greenland and Antarctic, emphasizing the necessity for operational ionospheric correction. The case studies also show that the accuracy of ice velocity estimates was significantly improved once the developed ionospheric correction techniques were integrated into the data processing flow. We demonstrate that the proposed ionosphere correction outperforms the traditionally-used approaches such as the averaging of multi-temporal data and the removal of obviously affected data sets. For instance, it is shown that about one hundred multi-temporal ice velocity estimates would need to be averaged to achieve the estimation accuracy of a single ionosphere-corrected measurement.;In Chapter 4, we evaluate the necessity and benefit of ionospheric-correction for L-band InSAR-based permafrost research. In permafrost zones, InSAR-based surface deformation measurements are used together with geophysical models to estimate permafrost parameters such as active layer thickness, soil ice content, and permafrost degradation. Accurate error correction is needed to avoid biases in the estimated parameters and their co-variance properties. Through statistical analyses of a large number of L-band InSAR data sets over Alaska, we show that ionospheric signal distortions, at different levels of magnitude, are present in almost every InSAR dataset acquired in permafrost-affected regions. We analyze the ionospheric correction performance that can be achieved in permafrost zones by statistically analyzing correction results for large number of InSAR data. We also investigate the impact of ionospheric correction on the performance of the two main InSAR approaches that are used in permafrost zones: (1) we show the importance of ionospheric correction for permafrost deformation estimation from discrete InSAR observations; (2) we demonstrate that ionospheric correction leads to significant improvements in the accuracy of time-series InSAR-based permafrost products.;Chapter 5 summarizes the work conducted in this dissertation and proposes next steps in this field of research.
机译：电离层已被确定为星载合成孔径雷达（SAR）数据和SAR干涉测量法（InSAR）的重要误差源，特别是对于在例如L波段或P波段工作的低频SAR任务而言。开发有效的电离层效应校正算法仍然是遥感研究的一个活跃的主题。本文的重点是开发鲁棒而准确的SAR和InSAR数据电离层校正技术，并评估这些技术在冰冻圈研究领域（如冰川冰速跟踪和多年冻土变形监测）的益处。由于这两个主题都主要涉及电离层经常活跃且以湍流为特征的高纬度地区，因此电离层校正对于这些应用尤其重要。；在第1章介绍了研究主题之后，第2章将讨论电离层中的开放性问题。校正，包括与基线引起的光谱偏移有关的处理问题。大基线对分裂频谱InSAR技术的影响已被彻底评估，并提出了补偿这种影响的有效解决方案。此外，提出了一种多子带方法来提高算法的鲁棒性和准确性。展示了选定的案例研究，目的是演示所开发算法的性能。在第三章中，已开发的电离层校正技术被用于优化基于InSAR的格陵兰和南极大冰盖的冰速测量。提出了一些案例研究，以证明和验证所提出的校正算法在冰速应用中的有效性。结果表明，电离层信号可能大于格陵兰和南极内部的实际冰川运动信号，从而强调了进行电离层校正的必要性。案例研究还表明，一旦将已开发的电离层校正技术集成到数据处理流程中，冰速度估算的准确性将大大提高。我们证明了拟议的电离层校正优于传统方法，如平均多时相数据和去除明显受影响的数据集。例如，表明要对单个电离层校正测量的估计精度进行平均，需要平均约一百次的多时冰速估算值。在第四章​​中，我们评估了对电离层校正的必要性和好处。基于L波段InSAR的多年冻土研究。在多年冻土带中，基于InSAR的表面变形测量值与地球物理模型一起用于估算多年冻土参数，例如活动层厚度，土壤冰含量和多年冻土退化。需要精确的错误校正，以避免估计参数及其协方差特性出现偏差。通过对阿拉斯加上大量L波段InSAR数据集的统计分析，我们表明，在多年冻土灾区采集的几乎每个InSAR数据集中，电离层信号失真的幅度都不同。我们通过统计分析大量InSAR数据的校正结果，分析了在多年冻土带中可以实现的电离层校正性能。我们还研究了电离层校正对多年冻土区中使用的两种主要InSAR方法的性能的影响：（1）我们展示了电离层校正对于通过离散InSAR观测估算多年冻土变形的重要性； （2）我们证明了电离层校正可以极大地提高基于时间序列的InSAR多年冻土产品的准确性。;第5章总结了本文所做的工作，并提出了该研究领域的下一步工作。

著录项

  • 作者

    Liao, Heming.;

  • 作者单位

    University of Alaska Fairbanks.;

  • 授予单位 University of Alaska Fairbanks.;
  • 学科 Geophysics.;Remote sensing.
  • 学位 Ph.D.
  • 年度 2018
  • 页码 134 p.
  • 总页数 134
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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