Evaluation of Rational Function Model for High-Resolution KOMPSAT-5 SAR Imagery with Different Sizes of Virtual Grid and Reference Coordinate Systems

When a new spaceborne imaging mission is launched and operated, the generation of the rational function model (RFM), which simplifies the geometric relationship between the ground targets and image coordinates, is one of the important mechanisms to unify the image data with the other geospatial datasets. In this paper, the performance of the generated RFM for the KOMPSAT-5 satellite imagery was evaluated. High-resolution KOMPSAT-5 images whose spatial resolutions are about 1 meter were used for the experiments. During the RFM generation process, the general least squares adjustment and the Tikhonov regularization with the L-curve optimization were applied to initialize and optimize the RFM coefficients. From the physical sensor model for KOMPSAT-5, virtual grids were created and utilized as the control points for generating the RFM. Furthermore, appropriate sizes of virtual grids and the number of elevation layers were proposed. As a result of the experiments, an RFM having a precision better than 10⁻⁹ pixels could be generated from a virtual grid of 10 × 10 × 5. Moreover, the reference coordinate system of the control points did not significantly affect the performance of the RFM generation process.