Interferometric synthetic aperture radar (InSAR) has been used to quantify a range of surface and near surface physical properties in permafrost landscapes. Most previous InSAR studies have utilized spaceborne InSAR platforms, but InSAR datasets over permafrost landscapes collected from airborne platforms have been steadily growing in recent years. Most existing algorithms dedicated toward retrieval of permafrost physical properties were originally developed for spaceborne InSAR platforms. In this study, which is the first in a two part series, we introduce a series of calibration techniques developed to apply a novel joint retrieval algorithm for permafrost active layer thickness retrieval to an airborne InSAR dataset acquired in 2017 by NASA's Uninhabited Aerial Vehicle Synthetic Aperture Radar over Alaska and Western Canada. We demonstrate how InSAR measurement uncertainties are mitigated by these calibration methods and quantify remaining measurement uncertainties with a novel method of modeling interferometric phase uncertainty using a Gaussian mixture model. Finally, we discuss the impact of native SAR resolution on InSAR measurements, the limitation of using few interferograms per retrieval, and the implications of our findings for cross-comparison of airborne and spaceborne InSAR datasets acquired over Arctic regions underlain by permafrost.

中文翻译：

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永久冻土动力学观测站——第一部分：用于季节性沉降估计的 UAVSAR L 波段 InSAR 数据的后处理和校准方法

干涉合成孔径雷达 (InSAR) 已被用于量化多年冻土景观中的一系列地表和近地表物理特性。以前的大多数 InSAR 研究都使用了星载 InSAR 平台，但近年来从机载平台收集的永久冻土景观 InSAR 数据集一直在稳步增长。大多数现有的专门用于检索永久冻土物理特性的算法最初是为星载 InSAR 平台开发的。在本研究（两部分系列中的第一部分）中，我们介绍了一系列校准技术，该技术旨在将用于永久冻土活动层厚度检索的新型联合检索算法应用于 NASA 无人飞行器合成孔径在 2017 年获得的机载 InSAR 数据集阿拉斯加和加拿大西部的雷达。我们展示了如何通过这些校准方法减轻 InSAR 测量不确定性，并通过使用高斯混合模型对干涉相位不确定性进行建模的新方法来量化剩余的测量不确定性。最后，我们讨论了本地 SAR 分辨率对 InSAR 测量的影响、每次检索使用少量干涉图的局限性，以及我们的发现对在永久冻土层下的北极地区获取的机载和星载 InSAR 数据集进行交叉比较的影响。