灰度重心法对星敏感器星像点进行质心定位,存在周期性系统误差,且高斯半径越小,误差峰值越大。为了对该型误差进行补偿,以积分型高斯点扩散函数为理想模型,所生成的星像点作为参考灰度数据,在时域上对灰度重心法开展仿真分析,对系统误差进行曲面拟合,拟合结果经过一阶泰勒展开处理,获得了误差补偿模型。仿真结果表明补偿算法显著提高了质心定位精度,高斯半径小至0.35像素,补偿后的质心定位精度优于10⁻³像素。

A periodic systematic error exists in gray-weighted centroiding method used in star image spot processing of star tracker, which shows greater peak error with decrease of Gaussian radius. To get high-precision centroiding by means of compensation for this type of error, the integral-type Gaussian point spread function (PSF) was chosen as ideal model, from which the star image spots were simulated as reference gray data, then simulation experiments and analysis were carried out in the time domain, after surface fitting of system error data and the following treatment of first order Taylor expansion, the systematic error compensating model was finally obtained. The simulation results manifest that the compensation algorithm increases centroiding precision significantly, when the Gaussian radius drops to 0. 35 pixel, the centroiding precision is better than 10⁻³ pixel by using the centroiding compensation algorithm.