首页> 外文期刊>Journal of the Optical Society of America, A. Optics, image science, and vision >Phase retrieval of large-scale time-varying aberrations using a non-linear Kalman filtering framework
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Phase retrieval of large-scale time-varying aberrations using a non-linear Kalman filtering framework

机译:使用非线性Kalman滤波框架相位检索大规模时变差的大规模时变差

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摘要

This paper presents a computationally efficient framework in which a single focal-plane image is used to obtain a high-resolution reconstruction of dynamic aberrations. Assuming small-phase aberrations, a non-linear Kalman filter implementation is developed whose computational complexity scales close to linearly with the number of pixels of the focal-plane camera. The performance of the method is tested in a simulation of an adaptive optics system, where the small-phase assumption is enforced by considering a closed-loop system that uses a low-resolution wavefront sensor to control a deformable mirror. The results confirm the computational efficiency of the algorithm and show a large robustness against noise and model uncertainties. (C) 2020 Optical Society of America
机译:本文提出了一个计算效率高的框架,其中使用单焦平面图像获得动态像差的高分辨率重建。在假设相位像差很小的情况下,提出了一种非线性卡尔曼滤波器的实现方法,其计算复杂度与焦平面相机的像素数近似成线性关系。在自适应光学系统的仿真中测试了该方法的性能,通过考虑使用低分辨率波前传感器控制可变形反射镜的闭环系统,实现了小相位假设。结果证实了算法的计算效率,并显示了对噪声和模型不确定性的强大鲁棒性。(C) 2020美国光学学会

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