Mode wavefront restoration method based on neural network

Abstract

The invention discloses a mode wavefront restoration method based on a neural network, and the method comprises the steps: extracting the mass center offset and second-order moment information of a light spot, and fitting a nonlinear relation between the mass center offset and second-order moment of the light spot and a Zernike coefficient through the neural network; and finally, directly predicting a Zernike coefficient corresponding to the wavefront to be measured from the light spot centroid offset and the second-order moment information through a neural network. Compared with a traditional method, the method has the advantages that the second-order moment information of the light spots is extracted while the mass center offset of the sub-light spots is extracted, effective information in the sub-apertures is increased, the corresponding relation between the light spot information and the Zernike coefficient is fitted through the neural network, the detection precision of the Shack-Hartmann wavefront sensor is improved, and under the same recovery precision, the detection precision of the Shack-Hartmann wavefront sensor is improved. The requirement of a Shack-Hartmann sensor for the number of sub-apertures is reduced, and the method is expected to be used in the fields of dark and weak beacons, high-resolution wavefront measurement and the like.

Description

technical field [0001] The invention belongs to the technical field of optical information measurement, in particular to a neural network-based mode wavefront restoration method. Background technique [0002] The Shack-Hartmann wavefront sensor is the most common optical wavefront measurement device, which is mainly composed of a microlens array and a CCD located at the focal plane. It has the advantages of simple structure, high light energy utilization rate, and fast measurement speed. , are widely used in optical detection, laser beam diagnosis, adaptive optics, ophthalmology and other fields. The main working principle of the Shack-Hartmann wavefront sensor is to divide the incident wavefront through the microlens array, and focus each sub-wavefront on the CCD to form a spot array image, and then according to the spot intensity information collected by the photodetector The centroid offset of each sub-spot is calculated to estimate the corresponding local sub-wavefront ...

AI Technical Summary

Problems solved by technology

However, as the number of sub-apertures of the Shack-Hartmann wavefront sensor increases, the signal energy collected in a single sub-aperture decreases, and the signal-to-noise ratio of the spot will decrease, resulting in an increase in the calculation error of the spot centroid, resulting in wavefront restoration. The accuracy is reduced. It can be seen that there is a contradiction between the restoration accuracy and the sampling density of the Hartmann sensor, which limits the detection performance of the Hartmann sensor for low light conditions.

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