Star Identification Algorithm Based on Oriented Singular Value Feature and Reliability Evaluation Method

Abstract

A full-sky autonomous star identification algorithm aimed at solving the “lost-in-space” problem is presented in this paper. It mainly consists of two steps: an initial match step and a reliability evaluation step. Oriented singular value feature matching is adopted to search for corresponding candidates of the stars detected in the initial match. After obtaining the stars' initial match results, an evaluation method is applied to estimate the reliability of candidates from the star voting results, acquiring the final unique matching of stars in the image. Experiments show that our algorithm is more robust to star position noise and magnitude noise than the two conventional algorithms. In the simulations, our algorithm achieves an identification rate of 97.0% with 2-pixel star position noise and 0.3 Mv star magnitude noise, and also performs well with false stars in the field of view. In addition, the memory requirement and identification time of our method are acceptable for actual engineering projects.