Boltzmann entropy based star identification algorithm for star tracker

摘要

In this paper star identification has been formulated as a pattern recognition problem. Star patterns, as seen from spacecrafts, are represented as feature descriptor containing directional cosines of the guide-star, star indices and singular value for each star group. Eigenvalue based Boltzman entropy has been used to select the adjacent stars of the guide star to specify a star-pattern. The training patterns are kept in a reference catalog and used for comparing and classifying query patterns (star-groups). The effectiveness of eigenvalues (or singular values) as features has been shown with distribution histogram. Identification performance was tested with different level pixel error.