A rapid star map identification method based on ant colony clustering algorithm

In order to increase star map identification speed and successful rate for large field of view, a rapid star map identification method based on ant colony clustering algorithm is presented. This method adopts ant colony clustering algorithm to quickly carry out clustering analyze for star-points set, chooses the optimal class and draws one circle by the center of circle being every star point in this class and the radius being special angular distance, and then composes a set including all star points in circle. Then angular distance of two star points is solved in each star-points set, and completes the path optimization of sets by ant colony algorithm. At last, the rapid match and recognize is be done by comparing the result of optimization with the corresponding data in guidance star database. The experimental results show that, compared with existing identification methods, this method has a high recognition rate, good real-time performance and robustness, and it only needs a small content database.