Star Identification Based on Radial Triangle Mapping Matrix

In this paper, a novel star image recognition algorithm is proposed based on a voting scheme that utilizes a radial triangle mapping matrix pattern. Inspired by the radial and cyclic algorithm, the radial triangle mapping matrix pattern is rotation-invariant, and does not rely on a location star, which provides a new idea for the construction of rotation-invariant patterns. The algorithm is based on a geometric voting scheme in which the radial triangle group is considered as the basic voting element. The database optimization is used to reduce the memory requirement and improve the query efficiency by extracting the nonzero value of the pattern. During the identification period, the voting scheme can vote for the candidate stars through the radial triangles, which improves the robustness towards the noise. The proposed algorithm exhibits a 98.41% identification rate with 2.0-pixel standard deviation of position noises and 0.3-Mv magnitude noises. The experimental results of the simulation star image and real star image show that the proposed algorithm is quite more robust towards position noise, magnitude noise, and false star noise when compared with other comparing algorithms.