Tomography approach for multi-object adaptive optics.
Tomography approach for multi-object adaptive optics.
复制标题
多目标自适应光学断层扫描方法。
DOI：
10.1364/josaa.27.00a253
复制
发表时间：
2010
期刊：
影响因子：
--
通讯作者：
G. Rousset
中科院分区：
文献类型：
--
作者：
F. Vidal;E. Gendron;G. Rousset
多目标自适应光学（MOAO）是一种利用自适应光学（AO）在科学大视场中进行校正的解决方案。与许多宽视场AO方案一样，需要湍流体积的层析重建，以便计算要在所观察到的非常微弱的目标的专用方向上应用的MOAO校正。MOAO的特殊性在于通过多个波前传感器（WFS）对变形镜进行开环控制，这些波前传感器在不同方向上耦合到明亮的引导星。MOAO要求所有通道的交叉配准和断层重建器的计算都需要新的程序。我们提出了一种新的方法，称为“学习和应用（L&A）”，使我们能够检索的断层重建使用的天空波前测量从MOAO仪器。该方法也被用于校准离轴波前传感器和科学光路中的变形镜之间的配准。我们提出了一个程序，连接在不同的方向和测量直接在天空中所需的协方差矩阵重建所需的WFSs。我们提出的理论表达式的湍流空间协方差的波前斜率允许一个推导出任何湍流协方差矩阵之间的两个波前传感器。最后，我们讨论了测量的协方差矩阵的收敛问题，我们提出了使用减少的湍流参数的理论斜率协方差的基础上的数据的拟合，我们提出了一个完全建模的重建器的计算。
Multi-object adaptive optics (MOAO) is a solution developed to perform a correction by adaptive optics (AO) in a science large field of view. As in many wide-field AO schemes, a tomographic reconstruction of the turbulence volume is required in order to compute the MOAO corrections to be applied in the dedicated directions of the observed very faint targets. The specificity of MOAO is the open-loop control of the deformable mirrors by a number of wavefront sensors (WFSs) that are coupled to bright guide stars in different directions. MOAO calls for new procedures both for the cross registration of all the channels and for the computation of the tomographic reconstructor. We propose a new approach, called "Learn and Apply (L&A)", that allows us to retrieve the tomographic reconstructor using the on-sky wavefront measurements from an MOAO instrument. This method is also used to calibrate the registrations between the off-axis wavefront sensors and the deformable mirrors placed in the science optical paths. We propose a procedure linking the WFSs in the different directions and measuring directly on-sky the required covariance matrices needed for the reconstructor. We present the theoretical expressions of the turbulence spatial covariance of wavefront slopes allowing one to derive any turbulent covariance matrix between two wavefront sensors. Finally, we discuss the convergence issue on the measured covariance matrices, we propose the fitting of the data based on the theoretical slope covariance using a reduced number of turbulence parameters, and we present the computation of a fully modeled reconstructor.