Multi-looking, aimed at reducing data size and improving the signal-to-noise ratio, is indispensable for large-scale InSAR data processing. However, the resulting “Fading Signal” caused by multi-looking breaks the phase consistency among triplet interferograms and introduces bias into the estimated displacements. This inconsistency challenges the assumption that only unwrapping errors are involved in triplet phase closure. Therefore, untangling phase unwrapping errors and fading signals from triplet phase closure is critical to achieving more precise InSAR measurements. To address this challenge, we propose a new method that mitigates phase unwrapping errors and fading signals. This new method consists of two key steps. The first step is triplet phase closure-based stacking, which allows for the direct estimation of fading signals in each interferogram. The second step is Basis Pursuit Denoising-based unwrapping error correction, which transforms unwrapping error correction into sparse signal recovery. Through these two procedures, the new method can be seamlessly integrated into the traditional InSAR workflow. Additionally, the estimated fading signal can be directly used to derive soil moisture as a by-product of our method. Experimental results on the San Francisco Bay area demonstrate that the new method reduces velocity estimation errors by approximately 9 %–19 %, effectively addressing phase unwrapping errors and fading signals. This performance outperforms both ILP and Lasso methods, which only account for unwrapping errors in the triplet closure. Additionally, the derived by-product, soil moisture, shows strong consistency with most external soil moisture products.

中文翻译：

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对多视 InSAR 数据进行解缠误差和衰落信号校正


多观察旨在减小数据量和提高信噪比，对于大规模 InSAR 数据处理是必不可少的。然而，由多视引起的“衰落信号”打破了三重态干涉图之间的相位一致性，并在估计的位移中引入了偏差。这种不一致挑战了三重相 closure 中只涉及 unwraping errors 的假设。因此，解开来自三重态相位闭合的相位解缠误差和衰落信号对于实现更精确的 InSAR 测量至关重要。为了应对这一挑战，我们提出了一种减轻相位解缠误差和衰落信号的新方法。这种新方法包括两个关键步骤。第一步是基于三重相位闭合的堆叠，它允许直接估计每个干涉图中的衰落信号。第二步是基于 Basis Pursuit Denoising 的展开纠错，它将展开纠错转换为稀疏信号恢复。通过这两个程序，新方法可以无缝集成到传统的 InSAR 工作流程中。此外，估计的衰落信号可以直接用于得出作为我们方法的副产品的土壤水分。在旧金山湾区的实验结果表明，新方法将速度估计误差降低了约 9 %–19 %，有效地解决了相位展开误差和衰落信号。这种性能优于 ILP 和 Lasso 方法，后者仅考虑三元组闭包中的解包错误。此外，衍生的副产品土壤水分与大多数外部土壤水分产品显示出很强的一致性。