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为了解决星点在实际成像过程中能量分布的偏正态分布问题,提高星点中心的定位精度,提出了基于偏正态分布模型的点扩展函数(PSF)相关算法。该算法根据实际星图中星点的能量分布特征,建立与之相对应的PSF,利用相关的原理,找到与星点能量分布相似度最高的PSF,通过确定对应PSF的最大值位置实现对星点中心的定位。实验结果表明,在星图噪声为N(0,0.001)的仿真条件下,且星点中心在1pixel内随机分布时,偏正态PSF相关法的星点中心平均定位精度可达到0.04pixel,远小于质心法0.4pixel和高斯曲面拟合法的1.03pixel。由实验结果可知,该算法定位精度高于质心法和高斯曲面拟合法,具有较好的抗噪声性和稳定性,提高了星点中心定位精度。
In order to solve the problem of partial normal distribution of energy distribution in starfield and improve the localization accuracy of star point, a PSF (point spread function) algorithm based on partial normal distribution model is proposed. According to the energy distribution characteristics of the star point in the real star map, the PSF is established and the correlation principle is used to find the PSF with the highest similarity to the star point energy distribution. The algorithm determines the maximum value of the corresponding PSF Point the center of the positioning. The experimental results show that the average localization accuracy of the center of the star point of the PSF-based PSF method can reach 0.04 pixel when the star noise is randomly distributed within 1 pixel under the star noise of N (0,0.001) Less than 0.4 pixel of centroid method and 1.03 pixel of Gaussian surface fitting method. The experimental results show that the proposed algorithm has higher positioning accuracy than the method of centroid and Gaussian surface fitting, has better noise immunity and stability, and improves the positioning accuracy of the satellite center.