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Sparse Matrix Wavefront Reconstruction: Simulations and Experiments

机译:稀疏矩阵波前重建:模拟和实验

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Adaptive optics systems with Shack-Hartmann wavefront sensors require reconstruction of the atmospheric phase error from subaperture slope measurements, with every sensor in the array being used in the computation of each actuator command. This fully populated reconstruction matrix can result in a significant computational burden for adaptive optics systems with large numbers of actuators. A method for generating sparse wavefront reconstruction matrices for adaptive optics is proposed. The method exploits the relevance of nearby subaperture slope measurements for control of an individual actuator, and relies upon the limited extent of the influence function for a zonal deformable mirror. Relying only on nearby sensor information can significantly reduce the calculation time for wavefront reconstruction. In addition, a hierarchic controller is proposed to recover some of the global wavefront information. The performance of these sparse wavefront reconstruction matrices was evaluated in simulation, and tested on the Palomar Adaptive Optics System. This paper presents some initial results from the simulations and experiments.
机译:带有Shack-Hartmann波前传感器的自适应光学系统需要从子孔径斜率测量中重建大气相位误差,并且阵列中的每个传感器都用于计算每个执行器命令。对于具有大量执行器的自适应光学系统,此完全填充的重建矩阵可能会导致大量的计算负担。提出了一种用于自适应光学的稀疏波前重建矩阵的生成方法。该方法利用附近的子孔径斜率测量的相关性来控制单个致动器,并且依赖于区域变形镜的影响函数的有限程度。仅依靠附近的传感器信息可以大大减少波前重建的计算时间。此外,提出了一种分层控制器来恢复某些全局波前信息。在仿真中评估了这些稀疏波前重建矩阵的性能,并在Palomar自适应光学系统上对其进行了测试。本文提出了一些来自仿真和实验的初步结果。

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