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.