Computer vision plays a key role in measuring the relative posture and position between spacecrafts, especially in various close-range space tasks. As one of the essential steps for computer vision, camera calibration is important for obtaining precise three-dimensional contours of a space target. The focal length of on-orbit zoom cameras constantly changes. Thus, it is practical to calibrate the focal length rather than other intrinsic camera parameters. However, traditional calibration targets, such as checkerboards, cannot be used to calibrate a space camera in orbit. To address this problem, we propose a two-step process for focal length calibration. In the first step, the initial estimate of the camera focal length was generated with vanishing points obtained from the solar panels of satellites. In the second step, the initial solution was optimized by the particle swarm optimization algorithm. The results of the simulations and laboratory experiments confirmed the accuracy, flexibility, and good antinoise interference performance of the proposed method. Thus, the proposed method has practical significance for space tasks, such as space rendezvous-docking and on-orbit maintenance.

中文翻译：

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无目标空间变焦相机的高效两步焦距标定

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，尤其是在各种近距离太空任务中。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。在轨变焦相机的焦距不断变化。因此，校准焦距而不是其他固有的相机参数是实用的。然而，传统的校准目标，如棋盘格，不能用于校准在轨空间相机。为了解决这个问题，我们提出了一个焦距校准的两步过程。在第一步中，相机焦距的初始估计是通过从卫星的太阳能电池板获得的消失点生成的。第二步，初始解通过粒子群优化算法进行优化。仿真和实验室实验结果证实了该方法的准确性、灵活性和良好的抗噪声干扰性能。因此，所提出的方法对于空间任务，如空间交会对接和在轨维护具有实际意义。