A Hamming Distance and Spearman Correlation Based Star Identification Algorithm

This paper presents a novel star identification algorithm for a “lost-in-space” mode star tracker. The Spearman-correlation approach provides reliable recognition even when the captured images are swayed and biased from the onboard star pattern database. The hamming distance approach provides a shortlisted list of star IDs. Thus, the proposed combination of hamming distance and Spearman correlation provides a reliable and fast recognition. The achievable performance is evaluated by testing on simulated and real images.