应用形状因子特征的高效星图识别

Efficient star identification algorithm based on shape factor features

  • 摘要: 针对传统的三角形星图识别算法存在冗余匹配多、抗噪声性能差的问题,提出了一种应用形状因子特征的高效星图识别算法。该算法在传统的三角形算法基础上,引入了形状因子特征参数和方向信息,并择优选择视场内4颗观测星,组成一对观测三角形,进行星点匹配识别。与传统的三角形算法相比,该算法增加了星图识别时图像的特征信息量,降低了匹配时的冗余度,具有导航特征库存储空间小、识别速度快等优点。实验表明,在星点位置噪声标准偏差为2个像素、星等噪声标准偏差为0.7星等的仿真条件下,该算法的识别率均在99%以上;通过地面实验的实物验证,在300 MHz的FT-C6713的DSP硬件平台上,全天自主识别的平均运行时间约为47 ms,具有明显的优势。

     

    Abstract: In response to the problems which exist in traditional triangle star identification algorithms including redundant matching and poor anti-noise performance, an efficient star identification algorithm based on shape factor feature was proposed. The algorithm presents the shape factor characteristic parameter of triangle and the direction information based on traditional triangle algorithm. Based on the traditional triangle algorithm, this algorithm introduces the feature parameters of shape factor and the direction information, and selects 4 observation stars in the field of view to form a pair of observation triangles, and then performs star point matching and recognition. Compared with the traditional triangle algorithm, the algorithm proposed increases the feature information amount of the star map when identifying star, reduces the redundancy when matching, and has the advantages of small storage space and high identification speed. The experimental results show that under the simulation conditions of standard deviation of 2 pixels and standard noise of 0.7 magnitude at the star position, the identification rate of the algorithm is more than 99%. Through the physical verification of the ground experiment, the average time of self-identification of star map is about 47 ms in the operation based on the FT-C6713 DSP hardware platform of 300 MHz, which has obvious advantages over traditional triangle star identification algorithm.

     

/

返回文章
返回