Due to the limitations in the geometric accuracy of reference data and matching accuracy between images from different sensors, the conventional method of calibration may not perform well in terms of accuracy for an agile optical satellite (AOS) with submeter resolution. Due to the high mobility of an AOS, a cross-image pair (CIP) including a push-broom image and a swing scanning image for the same area could be collected. This letter developed a novel calibration method for an AOS, which is characterized using the constraints from the CIP instead of reference images covering a calibration site. In this method, the viewing angle of a charge-coupled device detector fit by two polynomials is introduced into a rigorous imaging model to establish the calibration model, and a bundle adjustment under the constraint of an aided digital surface model (DSM) is applied to solve the unstable calculation stemming from the strong correlation between the parameters of the coupled images. To verify the effectiveness of the method, experiments were conducted using the CIP simulated according to the rigorous imaging process of an AOS. In tests, the method achieved a high theoretical accuracy of better than 0.1 pixels.

The high flexibility of the agile satellite can significantly improve its ability to obtain data. Compared with ordinary satellite platforms, the imaging-scheduling is more important, and is the basis to ensure the efficiency and quality of data for the agile satellite. To be aimed at the multi-strip imaging-mode of the agile satellite, from the perspective of the image-quality, a imagingscheduling algorithm based on certain step-size search in the multi-strip imaging-mode of the agile satellite is proposed , and the influence of the selection of the imaging time-window on the multi-strip image quality is analyzed quantitatively through the experimental data. The results show that the optimal image data can be obtained through the image-scheduling algorithm.