一种改进的栅格星图识别算法

A modified grid algorithm for star map identification

针对传统的栅格算法提取的特征模式不能反映其内在相似程度进而影响星图识别准确性的问题,提出了一种改进的栅格算法。利用特征模式间的度量函数反映不同特征模式之间的相似程度,解决了传统算法中由于位置量测误差造成的影响。根据实际情况建立了仿真环境,进行了仿真实验。结果表明:当星点位置噪声大于1.5像素时,改进算法的星图识别成功率明显高于现有的栅格算法;在存在"假星"的情况下改进算法的星图识别成功率优于现有的算法,验证了算法的有效性。

Considering that the characteristic pattern extracted by traditional grid algorithm can ’t reflect its internal similarity degree,which can affect the accuracy of star map recognition,a modified grid algorithm is proposed. The algorithm uses the metric functions derived from the characteristic patterns to reflect the similarity degree between different characteristic patterns,which solves the problem exists in feature mode extraction because influence of the position measurement error. Simulation environment according to the real situation is set up. The results indicate the star map identification success rate of the proposed method is obviously higher than the traditional algorithm when the star point position error is greater than 1. 5 pixels and the improved algorithm of star map recognition success rate is superior to the existing algorithms in the presence of＂artificial star＂,which shows the validation of the proposed algorithm.