Robust Camera Distortion Calibration via Unified RPC Model for Optical Remote Sensing Satellites

Abstract

On-orbit geometric calibration (GC) is always performed to compensate for geometric distortion from the satellite’s camera. However, the traditional GC method is complex and difficult to apply broadly due to its reliance on a rigorous physical model (RPM), which involves not only complex processing of attitude, orbit, and time, but also the transformation among multiple coordinate systems. Additionally, the RPM is closely related to designs of satellites and cameras, which increases the complexity of the GC, and thus reduces generalizability. This paper proposes a practical and robust GC method to prevent camera distortion based on a standardized rational polynomial coefficient (RPC) model. Through a series of innovations, including stepwise optimization, a priori gross error elimination, the adjustment model with angular resolution, and the correction for the bias field-of-view (FOV) distortion, we were able to achieve robust GC for camera distortion, as well as accurate splicing and registration among segmented images. Method validation using data from the linear-array camera of the ZiYuan3-02 satellite, and the area-array camera of the GaoFen-4 satellite, produced satisfactory results, indicating that our method effectively compensates for systematic geometric distortion such that consistent GC and accuracy comparable with that of traditional RPM-based methods can be obtained.