Volume XLII-3
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3, 1221-1228, 2018
https://doi.org/10.5194/isprs-archives-XLII-3-1221-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3, 1221-1228, 2018
https://doi.org/10.5194/isprs-archives-XLII-3-1221-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

  30 Apr 2018

30 Apr 2018

HYBRID GEOMETRIC CALIBRATION METHOD FOR MULTI-PLATFORM SPACEBORNE SAR IMAGE WITH SPARSE GCPS

G. Lv1,2, X. Tang2, B. Ai1, T. Li2, and Q. Chen2 G. Lv et al.
  • 1College of Geomatics, Shandong University of Science and Technology, Qingdao, China
  • 2Satellite Surveying and Mapping Application Center, NASG, Beijing, China

Keywords: SAR image, geometric calibration, R-D model, multi-platform, TerraSAR-X, TanDEM-X, Gaofen-3

Abstract. Geometric calibration is able to provide high-accuracy geometric coordinates of spaceborne SAR image through accurate geometric parameters in the Range-Doppler model by ground control points (GCPs). However, it is very difficult to obtain GCPs that covering large-scale areas, especially in the mountainous regions. In addition, the traditional calibration method is only used for single platform SAR images and can’t support the hybrid geometric calibration for multi-platform images. To solve the above problems, a hybrid geometric calibration method for multi-platform spaceborne SAR images with sparse GCPs is proposed in this paper. First, we calibrate the master image that contains GCPs. Secondly, the point tracking algorithm is used to obtain the tie points (TPs) between the master and slave images. Finally, we calibrate the slave images using TPs as the GCPs. We take the Beijing-Tianjin- Hebei region as an example to study SAR image hybrid geometric calibration method using 3 TerraSAR-X images, 3 TanDEM-X images and 5 GF-3 images covering more than 235 kilometers in the north-south direction. Geometric calibration of all images is completed using only 5 GCPs. The GPS data extracted from GNSS receiver are used to assess the plane accuracy after calibration. The results after geometric calibration with sparse GCPs show that the geometric positioning accuracy is 3 m for TSX/TDX images and 7.5 m for GF-3 images.