Novel star identification algorithm utilizing images of two star trackers

This paper investigates a star identification algorithm to improve the performance of especially a micro star tracker whose Field-of-view (FOV) is small. This algorithm is characterized by combining the images from two star trackers to identify the stars, rather than identifying the stars in each image separately. To improve the success ratio of star identification and attitude estimation accuracy, some novel ideas are added to the algorithm, such as the sequence of the algorithm based on both the FOVs and the mitigation of the problem of misalignments. By simulation results, the feasibility of that algorithm is evaluated.