Novel autonomous on-orbit calibration method for star sensors

Autonomous on-orbit calibration is critical for the development of star sensors. However, simultaneous estimation of optical parameters and star sensor distortion are a challenging task. The existing methods either aim at estimating the optical parameters (the focal length and the principal point) and ignoring the lens distortion, or first estimating the optical parameters, and then estimating lens distortion. These methods ignore the mutual influence between the optical parameters and lens distortion. To solve this problem, we used a non-linear optimization technique to simultaneously obtain the optimal performance of different star sensor parameters. First, the initial estimation of the optical parameters was obtained by using the maximum likelihood estimation method. Then, the linear least-squares solution was adopted to the initial estimate of the star sensor lens distortion. Finally, a globally optimal solution was used to refine all of the star sensor camera parameters. Comparing with the least-squares method and Samaans method under the same condition, the simulation results demonstrate that the proposed method is more robust and can achieve remarkable improvement in the star sensor calibration accuracy. In addition, the test results of the real nighttime images show that the calibration method can significantly improve the star identification performance.