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Large-Scale Multibaseline Phase Unwrapping: Interferogram Segmentation Based on Multibaseline Envelope-Sparsity Theorem

机译:大规模多基线相位展开:基于多基线包络稀疏定理的干涉图分割

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摘要

Multibaseline (MB) phase unwrapping (PU) is a critical processing step for the MB synthetic aperture radar interferometry (InSAR). Compared with the traditional single-baseline (SB) PU, MB PU has wider application scope on the study area with strong phase variation, because it can overcome the limitation of the Itoh condition. Since most of the MB PU methods need to process multiple interferograms simultaneously, the size of the input interferograms will pose unique challenges when it exceeds the limit of computational capabilities. Until now, the research achievements related to large-scale (LS) MB PU have been quite limited. To deal with such case, we propose a technique for applying the two-stage programming-based MB PU method (TSPA) proposed by Yu and Lan to the LS MB InSAR data set in this paper. To be specific, the MB $Lkappa $ -norm envelope-sparsity theorem is proposed and proved first, which gives a sufficient condition to exactly guarantee the consistency between local and global TSPA solutions. Afterward, based on the MB $Lkappa $ -norm envelope-sparsity theorem, we put forward an interferogram tiling strategy, whereby each LS interferogram in the input MB InSAR data set is partitioned into a set of several smaller sub-interferograms that can be unwrapped individually by TSPA in parallel or in series. Both theoretical analysis and experimental results show that the proposed tiling strategy is effective for the LS MB PU problem.
机译:多基线(MB)相位展开(PU)是MB合成孔径雷达干涉测量(InSAR)的关键处理步骤。与传统的单基线(SB)PU相比,MB PU具有克服Itoh条件的局限性,因此在研究领域的应用范围更广,相位变化也很大。由于大多数MB PU方法需要同时处理多个干涉图,因此,当输入干涉图的大小超出计算能力的限制时,它将带来独特的挑战。迄今为止,与大规模(LS)MB PU相关的研究成果还很有限。为了解决这种情况,我们提出了一种将Yu和Lan提出的基于两阶段编程的MB PU方法(TSPA)应用于本文的LS MB InSAR数据集的技术。具体而言,首先提出并证明了MB $ L kappa $-范数信封稀疏定理,这为充分保证本地和全局TSPA解决方案之间的一致性提供了充分的条件。然后,基于MB $ L kappa $-范数包络稀疏定理,我们提出了一种干涉图平铺策略,从而将输入MB InSAR数据集中的每个LS干涉图划分为几个较小的子干涉图集合,这些子干涉图可以由TSPA分别并行或串联解包。理论分析和实验结果均表明,所提出的平铺策略对于LS MB PU问题是有效的。

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