Persistent scatterer (PS) techniques are a set of important time-series tools for interferometric synthetic aperture radar (InSAR) that enable deformation analysis in highly decorrelated terrain. Detailed knowledge of the statistics of persistent scatterers in InSAR images is critical for the design of better techniques that will enable both the extraction of deformation in traditionally difficult regions as well as develop a better understanding of how performance of these algorithms relates to important system parameters. In this article, we characterize the backscatter statistics of both persistent and distributed scatterers over wavelength using data from X-band (COSMO-SkyMed), C-band (Sentinel-1), and L-band (ALOS) sensors. We show that popular distributions that have previously been used to fit SAR backscatter can effectively capture the returns from both PS and clutter, with the $\text {G}^0$ distribution being the most applicable across wavelength and scatterer type. Thus, our work paves the way for improved detection algorithms to be designed based on these distributions and also builds an initial foundation for developing a greater theoretical understanding of PS statistics.

中文翻译：

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波长上持久和分布式散射体的反向散射分布：来自 X、C 和 L 波段的结果

持久散射体 (PS) 技术是用于干涉合成孔径雷达 (InSAR) 的一组重要时间序列工具，可在高度去相关的地形中进行变形分析。详细了解 InSAR 图像中持久散射体的统计信息对于设计更好的技术至关重要，这些技术将能够提取传统困难区域的变形，并更好地了解这些算法的性能与重要系统参数的关系。在本文中，我们使用来自 X 波段 (COSMO-SkyMed)、C 波段 (Sentinel-1) 和 L 波段 (ALOS) 传感器的数据来表征波长范围内持久性和分布式散射体的反向散射统计数据。我们表明，以前用于拟合 SAR 反向散射的流行分布可以有效地捕获来自 PS 和杂波的回报，其中 $\text {G}^0$ 分布最适用于波长和散射体类型。因此，我们的工作为基于这些分布设计改进的检测算法铺平了道路，并为发展对 PS 统计的更深入的理论理解奠定了初步基础。