| Adaptive optics can effectively improve the performance of optical system by detecting and correcting the beam wavefront distortion.Adaptive optics with wavefront curvature detection is widely used in the field of astronomical imaging.The Laplace operator eigenmode control algorithm and depth neural network control algorithm for curvature adaptive optics were mainly studied.Firstly,the principle of grating wavefront curvature sensor was introduced,and the wavefront restoration algorithm with Laplace operator eigenmode was analyzed.On this basis,aiming at the problem of sensor spot signal extraction,an algorithm of automatic spot location and extraction based on the combination of the maximum class variance method and the centroid methodis proposed andverified.For wavefront curvature sensor,a wavefront measurement software was designed on the platform of visual studio 2013,based on Open CV library function and MFC library function.The functions of wavefront online measurement and offline data processing based on Laplace operator eigenmode method were realized.The wavefront control algorithm based on the eigenmode of Laplace operator was studied experimentally.The closed-loop wavefront correction experiment was carried out.The feasibility of this algorithm is verified by comparing the root mean square value of wavefront and peak valley value before and after correction.Finally,the algorithm of wavefront restoration and control based on depth neural network was studied.The normalized light intensity difference data of curvature sensor is used as the input of the network model,and the Zernike mode coefficient is used as the output of the network.Simulation results show that this method can recover wavefront accurately.Aiming at the curvature adaptive optical control technology,the wavefront detection,restoration and control methods are studied in depth,which has a good reference value for the practical application of this technology.Figure 35;Table 2;Reference 79... |
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