Fuzzy Decision-Based Star Identification Algorithm Using Star Magnitudes

Abstract

Traditional star identification algorithms use the angular separations as the identification feature, but the similar matches resulting from similar triangles degrade the identification efficiency and delay the process. To enhance the performances of the star identification algorithm, the information of the star magnitudes in star images is used to add a decision condition to exclude most of the similar triangle matches. For the grey levels of the stars in the star images are not linear to the visual magnitudes stored in the guiding catalogs, the statistics of the grey levels are used and a fuzzy decision strategy is adopted in judging the similar matches. The simulations demonstrate that the algorithm with the fuzzy decision process speeds up the process of star identification and increases the rate of success greatly.