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首页> 外文期刊>IEEE Transactions on Geoscience and Remote Sensing >Incorporating Temporary Coherent Scatterers in Multi-Temporal InSAR Using Adaptive Temporal Subsets
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Incorporating Temporary Coherent Scatterers in Multi-Temporal InSAR Using Adaptive Temporal Subsets

机译：使用自适应时间子集在多时相InSAR中合并临时相干散射体

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摘要

Multi-temporal interferometric synthetic aperture radar (MT-InSAR) is used for many applications in earth observation. Most MT-InSAR methods select scatterers with high coherence throughout the entire time series. However, as time series lengthen, inevitable changes in surface scattering lead to decorrelation, which systematically decreases the number of coherent scatterers. Here, we propose a novel method to detect and process temporary coherent scatterers (TCS) by subsequently analyzing the amplitude and the interferometric phase. Two hypothesis tests are developed for amplitude analysis in order to identify the moments of appearing and/or disappearing coherent scatterers. Based on the amplitude analysis, the parameters of interest are then estimated using the interferometric phase. An optimized adaptive temporal subset approach is proposed to improve the precision of the estimated parameters. If the scatterers are not evenly distributed over the area, a secondary (support) network is designed to improve the spatial point distribution. The main advantage of this method is the reliable extraction of a subset of time series without using any contextual information. Experimental results show that the TCSs significantly increase the number of observations for displacement monitoring and improve the change detection capability in urban construction areas.
机译：多时相干涉合成孔径雷达（MT-InSAR）在地球观测中有许多应用。大多数MT-InSAR方法会在整个时间序列中选择具有高相干性的散射体。但是，随着时间序列的延长，表面散射的不可避免变化会导致去相关，从而系统地减少了相干散射体的数量。在这里，我们提出了一种通过随后分析幅度和干涉相位来检测和处理临时相干散射体（TCS）的新颖方法。开发了两个假设测试用于幅度分析，以识别出现和/或消失的相干散射体的时刻。基于幅度分析，然后使用干涉相位估算感兴趣的参数。提出了一种优化的自适应时间子集方法，以提高估计参数的精度。如果散射体在该区域分布不均匀，则将设计辅助（支持）网络以改善空间点分布。此方法的主要优点是无需使用任何上下文信息即可可靠地提取时间序列的子集。实验结果表明，TCS显着增加了位移监测的观测数量，并提高了城市建筑区域的变化检测能力。

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