Improved genetic algorithm for intrinsic parameters estimation of on-orbit space cameras

Abstract

Computer vision plays a key role to measure the relative posture and position between the spacecrafts, especially in various important space tasks. As one of the essential steps for computer vision, camera calibration is important for obtaining precise three-dimensional contours of the space target. However, it is impossible to use the traditional calibration targets to calibrate the space camera in orbit. To solve this problem, in this paper, we attack the on-orbit space camera calibration problem by using two steps. First, we only use two images of the solar panel, which is a commonly used element of majority human-made spacecraft, to generate an approximate initial estimation of the camera intrinsic parameters. In order to improve the robustness and accuracy of our method, the second step optimizes the initial solution by using an improved genetic algorithm (IGA). Simulated and real experiments prove that the proposed method is accurate and flexible, and shows good robust performance. Therefore, our method has realistic significance for various space tasks.