Geometric Positioning Accuracy Improvement Method of Micro SAR Satellites With Large Positioning Errors

The rapid development of micro synthetic aperture radar (SAR) satellites provides a new means of all-day, all-weather, and high-frequency Earth observation. However, the geometric stability of micro SAR satellites is weak, and the geometric positioning error of SAR images is large. The traditional method improves the geometric positioning accuracy (GPA) of satellite images by adding well-distributed ground control points (GCPs), but it is time-consuming and laborious. This study proposed a method for improving the GPA of micro SAR satellites with large positioning errors. The proposed method designs a multilevel and multiscale SAR image matching framework, utilizes high-precision spaceborne SAR digital orthophoto image (DOM), and realizes high-precision virtual GCPs (VGCPs) extraction between micro SAR satellite images and DOM through image matching. Finally, using the matched VGCPs directly participate in the geometric correction to improve the GPA of the micro SAR images. The experiment adopted Gaofen-3 (GF-3) 10-m resolution DOM product as the control data. VGCPs were extracted and GPA was evaluated for five Luojia-2 (LJ-2) SAR images (3-m resolution, stripmap mode). The results show that the GPA of the LJ-2 image is at the kilometer level, and it can be improved to better than 5 m (relative to GF-3 DOM) after processing, which proves the validity and reliability of the proposed method. The proposed method can provide support for the cooperative processing of multisource SAR satellite images.