Ellipticity pivot star method for autonomous star identification

A new fast algorithm for autonomous star identification in the general lost-in-space case is developed based on optimized catalog. The proposed method takes advantage of singular value decomposition method and the accuracy angular separation information. The central idea is that a unique pattern is created for each of guide star so that the pattern recognition is simple and straightforward and the index entry reaches minimum. The unique pattern is comprised of ellipticity and angular separations between pivot star and adjacent stars. The method for selecting adjacent stars of pivot star and how to rank them is presented. Three series of simulations each of which included more than ten thousand star tracker orientations were performed by dividing the entire celestial sphere into small regions. The results support the validity of the proposed method that achieves higher identification rate with 99.999%.