杨颖, 张兰强, 饶长辉. 大视场地表层自适应光学系统性能评估方法对比分析[J]. 红外与激光工程, 2022, 51(7): 20210744. DOI: 10.3788/IRLA20210744
引用本文: 杨颖, 张兰强, 饶长辉. 大视场地表层自适应光学系统性能评估方法对比分析[J]. 红外与激光工程, 2022, 51(7): 20210744. DOI: 10.3788/IRLA20210744
Yang Ying, Zhang Lanqiang, Rao Changhui. Analysis of performance evaluation methods of wide-field ground-layer adaptive optics[J]. Infrared and Laser Engineering, 2022, 51(7): 20210744. DOI: 10.3788/IRLA20210744
Citation: Yang Ying, Zhang Lanqiang, Rao Changhui. Analysis of performance evaluation methods of wide-field ground-layer adaptive optics[J]. Infrared and Laser Engineering, 2022, 51(7): 20210744. DOI: 10.3788/IRLA20210744

大视场地表层自适应光学系统性能评估方法对比分析

Analysis of performance evaluation methods of wide-field ground-layer adaptive optics

  • 摘要: 在天文大视场高分辨率成像领域,对地表层自适应光学(Ground-Layer Adaptive Optics, GLAO)系统作出准确的理论评估是系统设计与优化的关键前提。在GLAO技术中,地表层湍流特性与导引星布局是影响系统性能的重要因素。针对不同湍流环境与导引星位置分布,基于空间频谱滤波理论和蒙特卡洛方法对GLAO系统进行理论分析与性能评价工作,从而验证两种方法的正确性与准确性。结果表明,两种模型得到的系统校正规律呈现明显的一致性。在一定条件下,两种方法数值模拟偏差最大不超过4.6%。空间频谱滤波原理将系统简化为线性模型,其计算速度更快,便于发现系统特征规律,但是该方法适用于导引星呈对称布局的系统性能分析,不适用于非对称排布的任意导星布局解析分析。蒙特卡洛方法结合真实系统的物理过程进行实时模拟,其导引星布局可以任意设置,对于系统实际运行状态的预测更加准确。在两种分析方法对比的基础上,进一步针对系统布局给出了初步的优化结果,相关工作对未来GLAO系统的设计与优化具有指导意义。

     

    Abstract: The performance evaluatation of ground layer adaptive opitcs (GLAO) is helpful for system design and optimization. The turbulence distribution and the layout of the guide stars (GSs) are the main factors affecting GLAO performance. Considering the impact of the turbulence distribution and the layout of GSs, the performance of GLAO was analysed and evaluated by comparing spatial frequency spectrum filtering theory and Monte Carlo simulation. The results show that the conclusions of the two methods are clearly consistent with an error margin of less than 4.6%. Spatial frequency spectrum filtering simplifies the system into a linear model and it is simpler and faster for the calculation, which is convenient for discovering the characteristic rules. However, the accuracy is slightly low if considering the noise and error in a real system. In addition, this method is suitable for analysing the system performance with a symmetrical GS layout. The Monte Carlo method is better for simulating the system running state in detail with a random GS layout. The brief results of the system performance analysis are given in the end by combining the two methods. The study will be useful for the system design and optimization of future GLAOs.

     

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