为了保障太阳杂光干扰下星像点质心定位的精度,本文提出了一种去阈值和杂光斜面噪声的质心定位新方法。首先,在星像点窗口内将太阳杂光灰度噪声建模为一个斜面。针对质心定位新方法,推导关于杂光斜面模型各参数估计误差的质心定位误差分析公式,尤其是关于开窗大小的函数关系。然后,基于窗口边缘像素给出杂光斜面模型的最小二乘参数估计公式。最后,采用传统的灰度重心法、去阈值灰度重心法和所提方法进行质心定位仿真测试,结果表明,所提方法的精度比传统灰度重心法和去阈值质心法的精度分别提高了2倍和15倍,是太阳杂光干扰下星像点质心定位的有效方法,具有一定的工程应用价值。

To secure the centroiding accuracy of star image spots under the interference of sun straylight noise, we proposed a new centroiding method featuring the subtraction of background threshold and straylight slope noise in this paper. First, the gray noise of sun straylight was modeled as a slope within the window of a star image spot. For the new centroiding method, the error analysis equation of centroiding was deduced regarding the parameter estimation errors of the straylight slope model, especially the function relation concerning the window size. Then, the least-square parameter estimation formulas for the straylight slope model were given based on the window edge pixels. Finally, simulation tests were conducted through three centroiding methods, namely, the traditional gray weighted centroiding method (GWCM), the threshold subtracted GWCM, and the new method. The testing results show that the centroiding accuracy of the proposed method is two times and fifteen times higher than that of the two traditional methods. In conclusion, the method proposed in this paper is an effective centroiding method for star image spots under the interference of sun straylight noise and has a certain value in engineering applications.