基于最优路径的多视场全天自主星图识别

Based on optimal path features and multiple fields of view (FOVs), a star recognition algorithm is developed to improve the recognition rate of star sensors with low cost and small FOV under all-sky autonomous recognition pattern. First, observed star images in multiple FOVs are fused through identification between images. Second, randomly distributed ant colonies are set at the positions of all the stars in the neighborhood of the main star. Then an optimal traversal path combining all these stars is acquired by iteration. The geometrical features of the path are applied for matching with guide star catalogue. Compared with several existing methods, the proposed algorithm provides high recognition rate and robustness against position and magnitude noise.