Previous research has demonstrated several successful meteorological applications of interferometric synthetic aperture radar (InSAR) by mapping high‐resolution precipitable water vapor (PWV) over large areas with satisfactory precision (e.g., 1–2 mm). InSAR, however, can only measure temporal changes in the PWV, that is, the differential PWV (ΔPWV) between two SAR acquisition epochs. The construction of absolute PWV maps using InSAR observations remains an intractable problem. We present here a new method for constructing high‐resolution PWV maps by fusing InSAR and global positioning system (GPS) measurements. Our method involves: (1) extracting temporal differences in the zenith wet delays (ΔZWD) from InSAR observations with the assistance of synchronous GPS measurements, and (2) using a constrained minimum variance estimator (CMVE) to construct the high‐resolution maps of the absolute ZWDs by fusing the InSAR‐ΔZWD and the GPS‐ZWD samples, and finally (3) transforming the high‐resolution ZWDs to PWVs using an elevation‐dependent proportionality. Only a single interferogram was needed in our method, so we did not use any temporal (i.e., time‐series) hypotheses, for example, we did not assume that the average value of the temporal turbulent ZWDs was equal to zero. We validated the new method over the Southern California region using four Sentinel‐1 interferograms related to eight SAR images acquired in different seasons and in different years. We also used synchronous GPS measurements from the Southern California integrated GPS network. Eight high‐resolution maps of PWVs related to the eight SAR acquisitions were generated, covering ∼250 km in area at a ∼160 m spatial resolution. Comparisons between the CMVE method and the other two methods (GPS‐only‐based interpolation and time‐series InSAR stacking) were conducted. Experimental results showed that the CMVE method performed significantly better than conventional methods for constructing high‐resolution PWV maps, which is of great interest to a wide community of geophysicists and meteorologists.

中文翻译：

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通过合并干涉合成孔径雷达和GPS测量获得的高分辨率水汽图

以前的研究已经通过在高分辨率上以令人满意的精度（例如1-2 mm）在大范围内绘制可沉淀水汽（PWV）的方式，展示了干涉式合成孔径雷达（InSAR）在气象方面的成功应用。但是，InSAR只能测量PWV的时间变化，即两个SAR采集时期之间的差分PWV（ΔPWV）。使用InSAR观测值构建绝对PWV映射仍然是一个棘手的问题。我们在这里介绍一种通过融合InSAR和全球定位系统（GPS）测量值来构建高分辨率PWV地图的新方法。我们的方法涉及：（1）在GPS同步测量的辅助下，从InSAR观测中提取天顶湿延迟（ΔZWD）的时间差异，（2）通过结合InSAR-ΔZWD和GPS-ZWD样本，使用约束最小方差估计器（CMVE）构造绝对ZWD的高分辨率图，最后（3）将高分辨率ZWD转换为PWV使用依赖于海拔的比例。在我们的方法中仅需要一个干涉图，因此我们没有使用任何时间（即时间序列）假设，例如，我们没有假设时间湍流ZWD的平均值等于零。我们使用与在不同季节和不同年份获取的八幅SAR图像相关的四张Sentinel-1干涉图，验证了南加州地区的新方法。我们还使用了来自南加州集成GPS网络的同步GPS测量。生成了与八次SAR采集有关的八张PWV高分辨率地图，以〜160 m的空间分辨率覆盖了约250 km的面积。进行了CMVE方法与其他两种方法（基于GPS的插值和时间序列InSAR叠加）之间的比较。实验结果表明，CMVE方法在构造高分辨率PWV地图方面的性能明显优于传统方法，这引起了地球物理学家和气象学家的广泛兴趣。