Teague Samuel, Chahl Javaan
J Opt Soc Am A Opt Image Sci Vis. 2024 Apr 1;41(4):654-663. doi: 10.1364/JOSAA.517943.
Wide angle star sensors are becoming more prevalent in aeronautics. A wide angle lens provides a greater field of view for star detection, but consequently incurs significant lens distortion. The effects of distortion complicate star identification, causing algorithms to fail or report false identifications. We address the issue of calibrating a wide angle star sensor without any specialized equipment, by analyzing two time-separated images captured from a static camera. An initial estimate of the focal length is obtained by observing the displacement of stars between the images. The focal length is subsequently used to build an initial estimate of camera intrinsics, and to identify stars in the image. A RANSAC-augmented Kabsch algorithm is implemented to determine camera orientation, while simultaneously removing false identifications. The identified stars are used to provide a precise estimate of camera focal length, before applying non-linear optimization in a radial search algorithm. The methodology was tested on two cameras, demonstrating the effectiveness of this algorithm in achieving a precise geometric calibration using real hardware, without any specialized calibration equipment.
广角星敏感器在航空领域正变得越来越普遍。广角镜头为恒星探测提供了更大的视野，但会产生显著的镜头畸变。畸变的影响使恒星识别变得复杂，导致算法失败或报告错误识别。我们通过分析从静态相机捕获的两张时间间隔的图像，解决了在没有任何专门设备的情况下校准广角星敏感器的问题。通过观察图像之间恒星的位移获得焦距的初始估计值。随后使用该焦距建立相机内参的初始估计值，并识别图像中的恒星。实施了一种RANSAC增强的Kabsch算法来确定相机方向，同时去除错误识别。在应用径向搜索算法进行非线性优化之前，使用识别出的恒星来精确估计相机焦距。该方法在两台相机上进行了测试，证明了该算法在使用实际硬件且无需任何专门校准设备的情况下实现精确几何校准的有效性。
