结合跟星系统成像特征的自动调焦系统设计

Design of auto-focusing system combining imaging characteristics of follow star system

对于恒星光斑成像,传统的梯度评价算法在重度离焦情况下梯度细节薄弱,难以识别正确的调焦方向。为了实现跟星系统对恒星的快速成像和可靠跟踪,建立了针对恒星成像特征进行评价的自动调焦系统,对系统的聚焦评价算法、自动调焦结构以及自动控制系统进行研究。通过跟星系统成像的灰度分布情况分析光斑图像梯度特征在正焦和离焦时的区别。根据恒星光斑成像灰度级差异变化的特点,将背景值纳入评价贡献,在传统的梯度评价函数中加入光斑信号灰度差异贡献。设计适用改进算法的调焦硬件结构和系统结构,利用步进电机和调焦底座组成调焦组件,通过计算控制单元驱动调焦组件实现自动调焦系统。利用搭载调焦系统的跟星装置进行实验和分析。实验结果表明:自动调焦装置能够在跟星系统中稳定地进行调焦工作,且改进算法相对于传统梯度算法有着更好的调焦方向性,在保持传统梯度算法67%灵敏度的同时,将局部极值点减小为0。改进算法不受梯度细节薄弱影响,能够在不同离焦程度下保持较好的调焦方向性和正焦灵敏性,跟星系统在搭载自动调焦装置后能够快速搜索合适焦距并进行大气光学特性测量。

In severe defocused cases during stellar facula imaging,traditional gradient evaluation algo⁃rithms often present weak gradient details and fail to correctly identify the direction of focus.Here,we de⁃signed an automatic focusing system for the evaluation of star imaging characteristics to realize the rapid im⁃aging and reliable tracking of stars based on a star-following system;moreover,we studied the focusing evaluation algorithm,automatic focusing structure,and automatic control of the system.Differences in the focus and focus gradient of a facula image were analyzed based on the grayscale distribution of the star system images.The background value was included in the evaluation contribution using the characteristics of grayscale differences in stellar facula imaging,and the grayscale difference contribution of the facula sig⁃nal was added to the traditional gradient evaluation function.To develop the automatic focusing system,three steps were followed:design of the focusing hardware and system structure adapted to the improved algorithm,construction of the focus assembly using a stepper motor and focus base,and the use of a calcu⁃lation control unit to drive the focus assembly.Experiments and analyses were conducted using a startracking device equipped with the focusing system.The experimental results revealed that the autofocus device could focus steadily on the star-tracking system.The improved algorithm presented better focus ori⁃entation than the traditional gradient algorithm.The local extreme point was reduced to zero while main⁃taining the 67%sensitivity of the traditional gradient algorithm.Thus,the improved algorithm was not af⁃fected by weak gradient details.It could maintain better focus directionality and focus sensitivity at differ⁃ent defocus levels.Equipped with an autofocusing ability,the developed star-tracking system can rapidly determine a suitable focal distance and assess atmospheric optical characteristics.