Geocoding is the procedure of finding the mapping between the Synthetic Aperture Radar (SAR) image and the imaged scene. The inverse form of the Range-Doppler (RD) model has been adopted to approximate the geocoding results. However, with advances in SAR imaging geodesy, its imprecise nature becomes more perceptible. The forward RD model gives reliable solutions but is time-consuming and unable to detect geometric distortions. This study proposes a highly optimized forward geocoding method to find the precise ground position of each image sample with a Digital Elevation Model (DEM). By following the intersection of the terrain and the so-called solution surface of an azimuth line, which can be locally approximated by a plane, it produces geo-location results almost identical to the analytical solutions of the RD model. At the same time, the non-unique geocoding solutions and the geometric distortions are determined. Deviations from the employed approximations are assessed, showing that they are highly predictable and lead to negligible range/azimuth residuals. The general robustness is verified by experiments on SAR images of different resolutions covering diversified terrains in the native or zero Doppler geometry. Comparisons with other forward algorithms demonstrate that, with extra geometric distortions detection ability, its accuracy and efficiency are comparable to them. For a Sentinel-1 IW burst of high topographic relief, the algorithm ends in a 3 s using 16 parallel cores, with an average residual smaller than one millimeter. Its impressive blend of efficiency, accuracy, and geometric distortion detection capabilities makes it ideal for large-scale remote sensing applications.

中文翻译：

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使用平面近似进行快速准确的 SAR 地理编码


地理编码是查找合成孔径雷达 （SAR） 图像和成像场景之间的映射的过程。已采用距离多普勒 （RD） 模型的逆形式来近似地理编码结果。然而，随着 SAR 成像大地测量学的进步，其不精确性变得更加明显。正向 RD 模型给出了可靠的解决方案，但非常耗时且无法检测几何变形。本研究提出了一种高度优化的正向地理编码方法，以使用数字高程模型 （DEM） 找到每个影像样本的精确地面位置。通过跟踪地形与方位线的所谓解面的交点（可以用平面局部近似），它产生的地理位置结果与 RD 模型的解析解几乎相同。同时，确定非唯一地理编码解决方案和几何变形。评估了与所采用的近似值的偏差，表明它们是高度可预测的，并且导致范围/方位角残差可以忽略不计。通过在覆盖原生或零多普勒几何中不同地形的不同分辨率的 SAR 图像上进行实验验证了总体鲁棒性。与其他正向算法的比较表明，具有额外的几何畸变检测能力，其准确性和效率与它们相当。对于高地形地貌的 Sentinel-1 IW 突发，该算法使用 16 个并行内核在 3 秒内结束，平均残差小于 1 毫米。它出色地融合了效率、准确性和几何变形检测功能，使其成为大规模遥感应用的理想选择。