Improved grid algorithm based on star pair pattern and two-dimensional angular distances for full-sky star identification

Abstract

A fast and robust star identification algorithm is proposed in this paper. The algorithm is derived from the grid algorithm but significantly improves the robustness by increasing the probability of the correct close neighbor star and reducing the pattern noise. Firstly, star pair patterns are constructed rather than star patterns. And a traversal method is adopted to find all the possible closest neighbor stars, which improves the robustness towards brightness noise. Secondly, the two-dimensional angular distance features are used instead of grid features in Cartesian coordinates to improve the robustness towards positional noise. The simulation results show that the proposed algorithm is quite robust to a variety of noise conditions. The identification rate of the proposed algorithm is higher than the grid algorithm and similar to the pyramid algorithm, while the identification speed is up to dozens times faster than the pyramid algorithm.