C-band Interferometric Synthetic Aperture Radar (InSAR) data are widely used to map coseismic deformation. However, phase unwrapping errors are commonly distributed near faults owing to decorrelation and steep phase gradients from short radar wavelengths. Here, we propose an improved SNAPHU phase-unwrapping algorithm that considers the prior information of the range offset gradients (P-SNAPHU) to overcome the constraints imposed by the phase continuity assumption. P-SNAPHU exploits median filtering of homogeneous pixels for initial denoising of range offset and then refines range offset gradients divisionally through saliency extraction. The derived gradients are used to estimate the expected values of the cost functions for the low-coherence fringes. The synthetic experiments show significant improvements in the phase-unwrapping accuracy of the P-SNAPHU method compared with classical unwrapping methods. We apply the P-SNAPHU method to unwrap Sentinel-1 coseismic interferograms of three large (Mw > 6.5) strike-slip earthquake events that the existing classical methods could not successfully unwrap. In the comparison of the unwrapped interferograms with the external global navigation satellite system (GNSS) displacements and those from the classical methods, we find that P-SNAPHU significantly reduces the phase unwrapping errors with the mean absolute error of 7.2, 2.3, and 1.8 cm for the 2023 Kahramanmaraş earthquake doublet, the 2016 Kumamoto earthquake, and the 2019 Ridgecrest earthquakes, respectively. Based on the unwrapped results derived from P-SNAPHU, an estimate is made regarding the shallow slip deficit of the 2023 Kahramanmaraş earthquake doublet, which is approximately 7%. Therefore, P-SNAPHU is useful for developing and applying C-band InSAR data for large earthquakes and volcanic activity.

中文翻译：

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Unwrap Intractable C-band Coseismic Interferograms：一种以距离偏移梯度为先验信息的改进 SNAPHU 方法


C 波段干涉合成孔径雷达 （InSAR） 数据广泛用于绘制同震形变。然而，由于短雷达波长的去相关和陡峭的相位梯度，相位解缠误差通常分布在断层附近。在这里，我们提出了一种改进的 SNAPHU 相位解缠算法，该算法考虑了范围偏移梯度 （P-SNAPHU） 的先验信息，以克服相位连续性假设施加的约束。P-SNAPHU 利用齐次像素的中值滤波对范围偏移进行初始降噪，然后通过显著性提取对范围偏移梯度进行划分细化。派生的梯度用于估计低相干条纹的成本函数的预期值。合成实验表明，与传统的展开方法相比，P-SNAPHU 方法的相位展开精度有了显著提高。我们应用 P-SNAPHU 方法解开了现有经典方法无法成功解开的三个大型 （Mw > 6.5） 走滑地震事件的 Sentinel-1 同震干涉图。在将展开的干涉图与外部全球导航卫星系统 （GNSS） 位移和经典方法的干涉图进行比较时，我们发现 P-SNAPHU 显著降低了相位展开误差，2023 年 Kahramanmaraş 地震双峰、2016 年熊本地震和 2019 年 Ridgecrest 地震的平均绝对误差分别为 7.2、2.3 和 1.8 cm， 分别。根据 P-SNAPHU 得出的解包结果，对 2023 年 Kahramanmaraş 地震双峰的浅层滑移赤字进行了估计，约为 7%。 因此，P-SNAPHU 可用于开发和应用用于大地震和火山活动的 C 波段 InSAR 数据。