A star identification algorithm based on simplest general subgraph

Subgraph isomorphism-based star identification algorithms require fewer stars than pattern-based algorithms and are suitable for practical application. Polygon algorithms and match group algorithms, as two typical subgraph isomorphism-based algorithms, both have disadvantages in efficiency and reliability. A novel star identification algorithm is presented in this study to solve this problem. We develop an analytical model to evaluate the validity of different subgraphs, which provides guidance to choose subgraphs. Based on the model, a series of effective and reliable subgraphs with different numbers of vertices, defined as the simplest general subgraphs, are chosen to achieve fast and direct star identification. The star matching strategy is divided into two basic steps. Based on the voting strategy, a star is initially identified by building match groups. It's further identified by building the simplest general subgraphs determined by the size of match groups. A verification approach of reprojection is adopted to improve the robustness of the algorithm. Compared with similar algorithms, the simulation test and night sky image test both show that the proposed algorithm is more robust to position noise, brightness noise, and false stars.