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Computationally efficient, practical implementation of tomographic minimum variance wavefront control using laser and natural guide stars for multi-conjugate adaptive optics

机译:计算有效,实用的层析成像最小方差波阵面控制,使用激光和自然导星进行多共轭自适应光学

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Minimum variance tomographic wavefront reconstruction is described in the literature as a 2-step process consisting of the estimation of dominant layers of distributed turbulence above the telescope, followed by least-squares fitting of this estimate onto deformable mirrors (DMs). The estimation problem is performed from wavefront sensor (WFS) measurements obtained from multiple guide stars. For many science cases, laser guide stars (LGSs) are required to increase sky coverage, but in this case a small number of low-order modes of the LGS WFS measurements are strongly corrupted by the uncertain position of the LGS on the sky and must be projected out from the range space of the turbulence-to-LGS WFS influence matrix. These modes are the global tip and tilt (TT) modes for each LGS WFS and possibly the differential focus modes between LGS WFSs. One possible approach to sense these null modes is to incorporate low-order natural guide star (NGS) WFS measurements in the estimation problem, although this complicates the practical implementation of the reconstruction algorithms. To overcome such complication, a split LGS/NGS wavefront control architecture has recently been proposed for multi-conjugate adaptive optics (MCAO). Such an architecture implements two separate control loops driven independently by the closed-loop LGS and NGS measurements, with distinct wavefront reconstruction algorithms and temporal filters applied to the LGS- and NGS-controlled modes. Control of the NGS modes is now a low dimensional problem, so that the reconstruction algorithm and servo bandwidth can be rapidly updated when the NGS asterism or the atmospheric conditions change. Sample simulation results illustrating the comparative performance of the integrated and split approaches are reviewed. Finally, a split Zernike-based architecture for multi-object adaptive optics (MOAO) is discussed.
机译:最小方差层析X射线波前重建在文献中描述为两步过程,包括估算望远镜上方分布湍流的主要层,然后将该估算值进行最小二乘拟合到可变形反射镜(DM)上。估计问题是根据从多个引导星获得的波前传感器(WFS)测量结果执行的。在许多科学案例中,都需要使用激光导星(LGS)来增加天空覆盖范围,但是在这种情况下,少数LGS WFS测量的低阶模式会由于LGS在天空中的不确定位置而受到严重破坏,因此必须从湍流到LGS WFS影响矩阵的范围空间中投影出来。这些模式是每个LGS WFS的全局倾斜和倾斜(TT)模式,可能是LGS WFS之间的微分聚焦模式。感知这些零模式的一种可能方法是将低阶自然导星(NGS)WFS测量合并到估计问题中,尽管这会使重建算法的实际实现复杂化。为了克服这种复杂性,近来已经提出了用于多共轭自适应光学器件(MCAO)的分离式LGS / NGS波前控制架构。这种架构实现了由闭环LGS和NGS测量独立驱动的两个单独的控制环路,并且将独特的波前重建算法和时间滤波器应用于LGS和NGS控制的模式。现在,NGS模式的控制是一个低维问题,因此,当NGS星号或大气条件发生变化时,可以快速更新重建算法和伺服带宽。审查了示例仿真结果,这些结果说明了集成方法和拆分方法的比较性能。最后,讨论了基于分裂的基于Zernike的多目标自适应光学(MOAO)架构。

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