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冻结大气湍流下自适应光学系统的预测校正性能
Performance of predictive correction for adaptive optics systems with frozen flow turbulence

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李正汉 1,2,3   李新阳 1,2 *  
文摘 针对自适应光学系统的校正滞后问题,提出预测校正方法,并对预测校正的鲁棒性进行了分析。冻结湍流假设下, Shack-Hartmann波前传感器的探测斜率一定程度保留了湍流的时域演变模式。利用横向风信息对斜率进行傅里叶平移,能实现斜率的预测。采用直接斜率法计算变形镜面形,能实现预测校正。仿真结果表明,提出的波前预测方法在横向风已知时,几乎能完全克服延迟导致的性能损失;当横向风需要估计时,该方法在风向估计准确的条件下能容忍1倍于自身的风速估计误差,或者在风速估计准确的条件下60°的风向估计误差,均能实现校正性能的提升;在风速和风向误差同时存在时,在较大的误差范围内依然能够提升系统的校正能力。
其他语种文摘 Accurate prediction of the atmospheric turbulence evolution in the next few sampling cycles can compensate for the time delay in the control systems of adaptive optics(AO)systems.In this paper,apredictive correction method in AO systems is proposed,and its robustness is analyzed. Under the frozen-flow assumption,the translational motion can be identified using the slope measurements of a Shack-Hartmann wavefront sensor(SHWS)in AO systems.Using the transverse wind information,prediction of the future slope can be achieved by Fourier translation.The shape of the deformable mirror (DM)can be calculated by the direct-gradient wavefront reconstruction algorithm.The aberrated wavefront is corrected by the DM.With a known transverse wind,the proposed predictive correction can provide a perfect compensation for the decline of the dynamic performance caused by delays in the control system.With estimated wind parameters,improvement of the correction efficiency can be obtained as long as the wind-velocity estimation error is less than the velocity itself,while the wind direction is estimated accurately,or the direction error is less than 60° while the wind speed is estimated accurately.With a simultaneous wind-velocity and direction error, the correction efficiency can still be improved within a large error range.
来源 光学精密工程 ,2018,26(3):548-555 【核心库】
DOI 10.3788/ope.20182603.0548
关键词 自适应光学 ; 预测校正 ; 冻结大气湍流假设 ; Shack-Hartmann波前传感器
地址

1. 中国科学院自适应光学重点实验室, 中国科学院自适应光学重点实验室, 四川, 成都, 610209  

2. 中国科学院光电技术研究所, 四川, 成都, 610209  

3. 中国科学院大学, 北京, 100049

语种 中文
文献类型 研究性论文
ISSN 1004-924X
学科 物理学
基金 国家自然科学基金资助项目
文献收藏号 CSCD:6208797

参考文献 共 25 共2页

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