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首页> 外文期刊>IEEE Transactions on Geoscience and Remote Sensing >A Temporal Phase Coherence Estimation Algorithm and Its Application on DInSAR Pixel Selection
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A Temporal Phase Coherence Estimation Algorithm and Its Application on DInSAR Pixel Selection

机译：时间相位相干估计算法及其在DInSAR像素选择中的应用

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摘要

Pixel selection is a crucial step of all advanced Differential Interferometric Synthetic Aperture Radar (DInSAR) techniques that have a direct impact on the quality of the final DInSAR products. In this paper, a full-resolution phase quality estimator, i.e., the temporal phase coherence (TPC), is proposed for DInSAR pixel selection. The method is able to work with both distributed scatterers (DSs) and permanent scatterers (PSs). The influence of different neighboring window sizes and types of interferograms combinations [both the single-master (SM) and the multi-master (MM)] on TPC has been studied. The relationship between TPC and phase standard deviation (STD) of the selected pixels has also been derived. Together with the classical coherence and amplitude dispersion methods, the TPC pixel selection algorithm has been tested on 37 VV polarization Radarsat-2 images of Barcelona Airport. Results show the feasibility and effectiveness of TPC pixel selection algorithm. Besides obvious improvements in the number of selected pixels, the new method shows some other advantages comparing with the other classical two. The proposed pixel selection algorithm, which presents an affordable computational cost, is easy to be implemented and incorporated into any advanced DInSAR processing chain for high-quality pixels identification.
机译：像素选择是所有先进的差分干涉合成孔径雷达（DInSAR）技术的关键步骤，这些技术直接影响最终DInSAR产品的质量。本文提出了一种用于DInSAR像素选择的全分辨率相位质量估计器，即时间相位相干性（TPC）。该方法能够与分布式散射体（DS）和永久散射体（PS）一起使用。研究了不同相邻窗口尺寸和干涉图组合类型[单主控（SM）和多主控（MM）]对TPC的影响。 TPC和所选像素的相位标准偏差（STD）之间的关系也已得出。结合经典相干和幅度色散方法，TPC像素选择算法已在巴塞罗那机场的37 VV极化Radarsat-2图像上进行了测试。结果表明TPC像素选择算法的可行性和有效性。与其他经典像素相比，新方法除了在选择像素数量方面有明显改进外，还显示出其他一些优势。提出的像素选择算法具有可承受的计算成本，易于实现，并且可以集成到任何高级DInSAR处理链中，以进行高质量的像素识别。

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