基于凸包和聚类分析的多基线Sar干涉图快速大尺度相位展开方法

Yang Lan, Hanwen Yu, M. Xing
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引用次数: 7

摘要

对于多基线合成孔径雷达(SAR)干涉测量(InSAR),多基线相位展开(PU)是一个重要步骤。随着MB InSAR的快速发展,MB InSAR系统的数据集规模越来越大。在“大数据”的情况下,MB PU可能会面临计算资源不足的新问题,或者需要花费太多的运行时间才能获得PU结果。为了处理这种情况,我们在H. Yu[1]的单基线(SB) PU方法(CHFLS)的启发下,提出了基于凸包和聚类分析的快速大规模MB PU方法(CCFLS)。CCFLS利用MB残基的聚类现象生成极性平衡的残基集合凸包,避免了在凸包内面积上耗费计算资源,从而可以快速得到高精度的PU解。理论分析和实验结果表明,CCFLS可以有效地减少内存消耗和计算时间。
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A Convex Hull and Cluster-Analysis Based Fast Large-Scale Phase Unwrapping Method for Multibaseline Sar Interferograms
For the multibaseline (MB) synthetic aperture radar (SAR) interferometry (InSAR), MB phase unwrapping (PU) is an important step. With the rapid development of MB InSAR, the size of the datasets from the MB InSAR system is becoming increasingly larger. Under the situation of "bigdata", MB PU may face new problems with insufficient computing resources, or take too much running time to get the PU result. In order to deal with such case, we propose a convex hull and cluster-analysis based fast large-scale MB PU method (CCFLS) with enlightened by the single baseline (SB) PU method (CHFLS) from H. Yu [1]. CCFLS uses the clustering phenomenon of the MB residues to generate the convex hull of residues set with balance polarity, and avoids spending the computation resources on the area within the convex hull, so that the high-precision PU solution can be quickly obtained. The theoretical analysis and experiment results indicate that CCFLS can effectively reduce memory consumption and calculation time.
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