一种非标定的快速星图识别方法

大多数现有算法在星敏感器光学系统参数标定不准确时,识别率显著降低。针对这种情况提出了一种无需标定参数的识别算法。该算法引入比例距离作为径向特征,角度作为环向特征。这两种特征不依赖焦距、主点等任何光学系统参数,仅和图像平面上的星点位置有关。识别时首先按照特征量进行初始匹配,然后利用FOV(Field of View)约束筛选待选星进行精确匹配。为了加快速度,精确匹配时引入了快速分组方法。仿真实验表明,该方法具有较快的识别速度,在没有光学系统参数的情况下,识别率可以达到97%。

A star identification algorithm for un-calibrated star sensor cameras

When optic parameters of star sensor are not accurate,identification rate of most star identification algorithms falls sharply.A new identification algorithm is presented for solving the problem.Rate distance is introduced as the radial pattern and angle as cyclic pattern.The patterns do not require any optic parameter such as the focal length,and the optical axis offsets.They are decided only by stars' location on the image.Two patterns are used for initial match firstly,and FOV(Field of View) restriction is used for accurate match.To speed up the search process,fast grouping method for candidate stars is proposed.Simulation is done to verify the performance and the result shows that the average runtime is short and identification rate reaches 97% without using optical parameters.