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An Improved Method of the Finite-Difference Sparse Phase Unwrapping

机译:一种有限差异稀疏相位展开的改进方法

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摘要

Phase unwrapping (PU) is a significant problem for reconstructing the deformation field during synthetic aperture radar interferometry analysis. The various 2-D PU algorithms can be divided into two categories: path-following methods and optimization-based methods. The former predefine an integration path in which the phase gradient is integrated to obtain the unwrapped results. The latter are path independent and error criterion oriented. The integration of the finite differences and the minimum cost flow solver describes a global optimization problem between the phase residues over closed spatial triangles computed over redundant neighboring edge sets. We propose a modified network using a simplified mathematical formulation for linear programming (LP) in the finite differences PU. Our algorithm has three major advantages over current methods. First, the modified network combines the Delaunay triangulation and K nearest points to avoid isolated regions in the PU process. Second, modified formulation of the LP solver can directly obtain the phase ambiguity cycles of all points without integration. Finally, the combination of the new network and modified LP can achieve better PU results than the other state-of-the-art techniques. We applied our method to synthetic and real data from January 24, 2020 Mw 6.7 earthquake in Doğanyol–Sivrice, Turkey to August 8, 2017 Mw 6.5 earthquake in Jiuzhaigou, China. Comprehensive comparisons validate the effectiveness of our method.
机译:相位展开(PU)是在合成孔径雷达干涉测量分析中重建变形场的重要问题。各种2-D PU算法可分为两类:路径跟踪方法和基于优化的方法。前者预定义的集成路径,其中集成了相位梯度以获得未包装的结果。后者是路径独立和导向的错误标准。有限差异的整合和最小成本流求解器描述了在冗余相邻边缘集合的闭合空间三角形上的相位残留之间的全局优化问题。我们在有限差异PU中使用简化的数学制定来提出修改的网络,用于线性编程(LP)。我们的算法具有超过当前方法的三个主要优点。首先,修改的网络组合了Delaunay三角测量和k最接近点以避免PU过程中的隔离区域。其次,LP求解器的修改配方可以直接在不整合的情况下直接获得所有点的相模糊度周期。最后,新网络和修改的LP的组合可以实现比其他最先进的技术更好的PU结果。我们将我们的方法从1月24日,2020 MW 6.7地震到Doğnyol-Sivrice,土耳其到2017年8月8日,2017年8月8日综合和实际数据。综合比较验证了我们方法的有效性。

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