一种基于Hausdorff距离的改进星图识别方法

针对基于Hausdorff距离HD(Hausdorff Distance)识别法存在识别速度慢和对星敏感器镜头旋转特别敏感的问题,提出了一种基于Hausdorff 距离进行星图识别的改进算法,它采用有向距离和绝对距离相结合的方法,利用恒星的空间结构信息,构建有向距离匹配模型;根据镜头旋转特性,建立绝对距离抗旋转模型;对两种模型测试研究确定加权因子,同时选取恰当的匹配识别门限,最终实现匹配识别的性能达到最优.仿真实验结果表明,改进后的算法不但保持了原有算法的高识别率,强抗噪性,而且还具有更快的识别速度和好的抗旋转特性.它在实际工程中已得到成功应用.

Improved star map identification algorithm based on Hausdorff distance

To solve two problems that the identification algorithm based on Hausdorff distance have the slow recognition speed and being very sensitive for the rotation of lens of star sensor, an improved star map identification algorithm based on Hausdorff distance was proposed. In this method, vector distance was combined with scalar distance. The information of star dimensional configuration was used, and a matching model of vector distance was constructed. According to the rotation peculiarity of lens, a anti-rotation model of scalar distance was set up, the weighted factor was ascertained by testing and researching the two models, right matching and recognizing threshold was choosed, and the final optimum performance of recognition was achieved. The simulation results show that it improved algorithm not only had good identification rate and strong anti-noise characteristic of original algorithm but also had better recognition speed and good anti-rotation characteristic. It was used successfully in the actual projects.