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.

中文翻译：

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在轨空间相机内参数估计的改进遗传算法

摘要 计算机视觉在测量航天器之间的相对姿态和位置方面起着关键作用，尤其是在各种重要的空间任务中。作为计算机视觉的基本步骤之一，相机标定对于获得空间目标的精确三维轮廓非常重要。然而，无法使用传统的标定目标来标定在轨空间相机。为了解决这个问题，在本文中，我们通过两个步骤来解决在轨空间相机标定问题。首先，我们只使用太阳能电池板的两个图像，这是大多数人造航天器的常用元素，来生成相机内在参数的近似初始估计。为了提高我们方法的鲁棒性和准确性，第二步通过使用改进的遗传算法 (IGA) 优化初始解决方案。仿真和真实实验证明，该方法准确灵活，具有良好的鲁棒性。因此，我们的方法对各种空间任务具有现实意义。