采用最大背景估计的星敏感器图像处理方法

星图处理是星敏感器运行的基础,而杂光干扰是影响星敏感器图像处理的主要因素之一,是算法设计需要重点考虑的干扰源。为消除杂光干扰的影响,通过分析星图中目标及背景的特征,根据星点二维高斯分布模型构造了权值参考函数,改进了最大化背景估计模型,设计了欧几里德四象限旋转对称的掩模,辅以图像分割、去噪,构成采用最大背景估计的星敏感器图像处理算法。另外采用了星点提取率、虚警率、极限探测星等、单星定位精度和仿真时序综合评价星图处理算法性能。实验证明该图像处理算法星点提取率高、虚警率低、单星定位精度高、抗杂光干扰性能优异且具有通用性。

Image processing of star sensor based on maximum background estimation

Stray light interference is one of the main effect factors for image process of star sensor. To eliminate the effect of stray light,features of targets and background in star image were analyzed. According to 2D-Gaussian distribution,a weight reference function was constructed,and maximum background estimation model was improved. A Euclid four-quadrant rotational symmetric mask was designed,combining with image segmentation and denoising,an image processing algorithm of star sensor based on maximum background estimation was proposed. A comprehensive method was adopted to evaluate the performance of the image process algorithm,including star detection ratio,false-alarm ratio,star detection limit magnitude,single star position accuracy and timing sequence. The experiment results prove that the proposed algorithm is effective and universal for star detection,also robust for stray light interference.