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Optimum Image Formation for Spaceborne Microwave Radiometer Products

机译：星载微波辐射计产品的最佳成像

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摘要

This paper considers some of the issues of radiometer brightness image formation and reconstruction for use in the NASA-sponsored Calibrated Passive Microwave Daily Equal-Area Scalable Earth Grid 2.0 Brightness Temperature Earth System Data Record project, which generates a multisensor multidecadal time series of high-resolution radiometer products designed to support climate studies. Two primary reconstruction algorithms are considered: the Backus–Gilbert approach and the radiometer form of the scatterometer image reconstruction (SIR) algorithm. These are compared with the conventional drop-in-the-bucket (DIB) gridded image formation approach. Tradeoff study results for the various algorithm options are presented to select optimum values for the grid resolution, the number of SIR iterations, and the BG gamma parameter. We find that although both approaches are effective in improving the spatial resolution of the surface brightness temperature estimates compared to DIB, SIR requires significantly less computation. The sensitivity of the reconstruction to the accuracy of the measurement spatial response function (MRF) is explored. The partial reconstruction of the methods can tolerate errors in the description of the sensor measurement response function, which simplifies the processing of historic sensor data for which the MRF is not known as well as modern sensors. Simulation tradeoff results are confirmed using actual data.
机译：本文考虑了辐射计亮度图像形成和重建的一些问题，这些问题可用于NASA资助的校准无源微波日均面积可扩展地球网格2.0亮度温度地球系统数据记录项目，该项目生成了一个多传感器多年代际时间序列，分辨率辐射计产品旨在支持气候研究。考虑了两种主要的重建算法：Backus–Gilbert方法和散射仪图像重建（SIR）算法的辐射计形式。将这些与传统的“桶中滴”（DIB）网格图像形成方法进行了比较。给出了各种算法选项的权衡研究结果，以选择网格分辨率，SIR迭代次数和BG伽玛参数的最佳值。我们发现，尽管与DIB相比，两种方法均能有效提高表面亮度温度估计值的空间分辨率，但SIR所需的计算量却大大减少。探索了重建对测量空间响应函数（MRF）准确性的敏感性。该方法的部分重构可以容忍传感器测量响应功能的描述中的错误，从而简化了历史传感器数据的处理，而对于这些传感器，MRF和现代传感器都不为人所知。仿真折衷结果使用实际数据进行确认。

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