干涉型合成孔径雷达时间序列分析的多弧平差方法

IF 4.4
Bingquan Han;Chen Yu;Zhenhong Li;Chuang Song;Xiaoning Hu;Jie Li
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引用次数: 0

摘要

利用干涉合成孔径雷达(InSAR)精确测量地表变形速度对于理解地球物理过程至关重要。然而,传统方法在捕捉长距离的细微变形时往往面临挑战,因为在展开过程中引入的误差可能会累积过大的空间范围。本研究介绍了一种多弧平差(MAA)方法,旨在减轻这些误差,特别是在高精度监测场景中,速度对参考点的位置很敏感。仿真结果表明,MAA方法显著优于传统方法,在噪声条件和复杂相位展开场景下均能大幅降低均方根。此外,将MAA方法集成到断层滑动反演中,提高了断层滑动分布估计的精度。这些发现强调了MAA方法在具有挑战性的环境中增强变形速度测量的潜力,使其成为大地测量和构造研究的宝贵工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Multiarc Adjustment Method for Interferometric Synthetic Aperture Radar Time-Series Analysis
Accurately measuring surface deformation velocity using interferometric synthetic aperture radar (InSAR) is crucial for understanding geophysical processes. However, traditional methods often face challenges in capturing subtle deformations over long distances, as errors introduced during unwrapping can accumulate overextended spatial extents. This study introduces a multiarc adjustment (MAA) method aimed at mitigating these errors, especially in high-precision monitoring scenarios, where velocities are sensitive to the location of the reference point. Simulation results demonstrate that the MAA method significantly outperforms the traditional method, achieving substantial reductions in rms under noisy conditions and complex phase unwrapping scenarios. Furthermore, integrating the MAA method into fault slip inversion improves the accuracy of slip distribution estimations. Applications to real datasets from the southern Tibet region and the San Andreas Fault further validate the MAA method’s effectiveness. These findings underscore the MAA method’s potential to enhance deformation velocity measurements in challenging environments, establishing it as a valuable tool for geodetic and tectonic studies.
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