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A Small-Baseline InSAR Inversion Algorithm Combining a Smoothing Constraint and $L_1$ -Norm Minimization

机译:结合了平滑约束和 $ L_1 $ -Norm最小化的小基线InSAR反演算法

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摘要

Atmospheric artifacts and phase unwrapping errors have unfavorable effects on differential synthetic aperture radar interferometry (DInSAR) deformation monitoring. In this letter, we present an alternative small-baseline DInSAR inversion algorithm, velocity-constraint L-1-norm minimization. The proposed algorithm improves the robustness of time series deformation estimation by combining a smoothing constraint and L-1-norm minimization. The smoothing constraint can minimize temporal atmospheric artifacts, and the L-1-norm minimization outperforms L-2-norm minimization in the presence of phase unwrapping errors. The iteratively reweighted least square algorithm is employed to adjust the weights of DInSAR observations and smoothing constraints in L-1-norm minimization. The proposed algorithm is validated using simulated data and TerraSAR-X data. The experimental results show that the proposed algorithm is suitable for the inversion of approximately linear deformation processes affected by both atmospheric artifacts and unwrapping errors.
机译:大气伪影和相位解开误差对差分合成孔径雷达干涉测量(DInSAR)变形监测有不利影响。在这封信中,我们提出了另一种小基线DInSAR反演算法,即速度约束L-1-norm最小化。提出的算法通过结合平滑约束和L-1-范数最小化来提高时间序列变形估计的鲁棒性。在存在相位展开误差的情况下,平滑约束可以最小化时间上的大气伪影,并且L-1-范数的最小化胜过L-2-范数的最小化。迭代加权最小二乘算法用于调整DInSAR观测值的权重和L-1-范数最小化中的平滑约束。使用模拟数据和TerraSAR-X数据对提出的算法进行了验证。实验结果表明,该算法适用于同时受大气伪影和解包误差影响的近似线性变形过程的反演。

著录项

  • 来源
    《IEEE Geoscience and Remote Sensing Letters》 |2019年第7期|1061-1065|共5页
  • 作者单位

    Univ Chinese Acad Sci, Beijing 100049, Peoples R China|Chinese Acad Sci, Inst Elect, Space Microwave Remote Sensing Syst Dept, Beijing 100190, Peoples R China;

    Chinese Acad Sci, Inst Elect, Space Microwave Remote Sensing Syst Dept, Beijing 100190, Peoples R China;

    Chinese Acad Sci, Inst Elect, Space Microwave Remote Sensing Syst Dept, Beijing 100190, Peoples R China;

    Chinese Univ Hong Kong, Inst Space & Earth Informat Sci, Hong Kong, Peoples R China|Minist Land & Resources, Key Lab Urban Land Resources Monitoring & Simulat, Shenzhen 518034, Peoples R China;

    Chinese Univ Hong Kong, Inst Space & Earth Informat Sci, Hong Kong, Peoples R China;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Deformation monitoring; small baseline (SB); synthetic aperture radar interferometry (InSAR);

    机译:变形监测;小基线(SB);合成孔径雷达干涉仪(InSAR);

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