Fast and accurate SAR geocoding with a plane approximation

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.