Global Iterative Geometric Calibration of a Linear Optical Satellite Based on Sparse GCPs

Independent methods for geometric calibration (GC) have become an important research direction in the field of optical satellite technology. The main purpose of this research is to eliminate dependence on ground calibration sites using relative constraints between images. Based on a systematic analysis of these relative constraints, we found that it was difficult, if not impossible, to completely eliminate ground constraints, although the number of ground control points (GCPs) required can be greatly reduced. To achieve practical GC with high accuracy and low cost, we proposed a new method to compensate for systematic errors in linear optical satellite data acquisition using only the relative constraints between two overlapped images, namely, the corresponding elevation constraints and sparse GCPs. We first demonstrated the feasibility of GC with relative constraints and established an optimized GC model suitable for these relative constraints. We then presented a global iterative method to eliminate inaccuracies in internal calibration caused by the different distributions of GCPs within two images. The nadir (NAD) linear camera on board the Zi-Yuan 3 (ZY-3) satellite was used to evaluate the feasibility of the presented GC method; the results indicated that the present method effectively compensated for systematic errors. Thus, this article demonstrated the feasibility of GC without calibration sites.