红外星图预处理及星点定位精度分析

红外星图是白天观星获取的原始数据，图中含有单点噪声和条纹噪声等多种噪声，严重影响了后续的星点提取和质心定位。针对外场观星获取的红外星图，进行了星图预处理，并分析了星点定位精度。提出了单点噪声的检测与补偿算法和条纹噪声的列均值偏移校正（CMOC）算法，还采用Wiener2 和Top-hat 组合滤波方法对星图进行进一步滤波去噪，最后使用在观测星图中加入理想模拟星点的方法计算了星点定位精度。实验结果表明，预处理算法有效抑制了红外星图中的各种噪声，星点目标峰值信噪比最多由4.7 提高到了31.3，模拟的2 等星的星点定位标准偏差量级为1/30 pixel 水平，满足工程应用的精度要求。

Preprocessing of infrared star map and position accuracy analysis of star point

As the raw data of daytime star gazing, there are single-point-noise, stripe noise and some other noise in infrared star map, which severely affect the sequential star-point extraction and centroid localization. According to the star map of field star gazing, methods of star map denoising and star-point position accuracy analysis were studied in the paper. An algorithm for single-point-noise detecting and compensating and a colum mean offset correction (CMOC) algorithm for stripe denoising were proposed. Then, a complex filtering method of Wiener 2 and Top-hat was used to denoise the star map furtherly. At last, a method of adding ideal simulated star-point to observation star map was used to calculate the starpoint centroid position accuracy. Experimental results indicate that the preprocessing method could denoise various kinds of noise in infrared star map, and the peak signal-to-noise ratio of star point target could be raised from 4.7 to 31.3, and the standard error of star-point localization of simulated 2 Mv star could achieve 1/30 pixel, which satisfies the accuracy of engineering application.