CN114964522A - Hartmann wavefront restoration method based on pupil mapping model - Google Patents

Abstract

The invention provides a Hartmann wavefront restoration method based on a pupil mapping model. According to the incident pupil information of the Hartmann wavefront sensor, the time domain/spatial domain non-uniformity characteristics of the pupil distribution are extracted through data processing. The resulting sub-aperture centroid deviation, select a sub-aperture with a small centroid deviation, and complete the wavefront restoration in the form of a reconstructed mode restoration matrix. The method comprehensively considers the non-uniform characteristics of the pupil, and is especially suitable for the Hartmann wavefront detection of pupils with dynamic intensity distribution characteristics. At the same time, it can also provide certain auxiliary functions for the accurate correction of aberrations under the dynamic intensity distribution pupil and the stable decoupling of multiple correctors.

Description

A Hartmann Wavefront Restoration Method Based on Pupil Mapping Model

technical field

The invention belongs to the technical field of optical information measurement, in particular to a Hartmann wavefront restoration method based on a pupil mapping model.

Background technique

The Hartmann wavefront sensor is a wavefront measurement method with both high precision and high sensitivity, and has been successfully used in adaptive optics, optoelectronic system integration, optical detection and other fields. The Hartmann wavefront sensor differentiates the optical wavefront in the form of a sub-aperture array, and extracts the sub-aperture slope, the second-order moment of the sub-wavefront, and the sub-aperture light spot inversion information from the sub-spot to calculate the phase information of the complete wave front (ie, wavefront information).

When the pupil intensity distribution of the beam to be measured has spatial/temporal non-uniformity, the pupil intensity distribution contributes to the sub-spot imaging, which may cause the sub-spot morphology to be degraded or even missing, increase the extraction error of the wavefront detection information, and affect the wavefront Recovery results. Therefore, for the wavefront detection of the entrance pupil with non-uniform intensity distribution, it is necessary to develop corresponding wavefront recovery methods to improve the wavefront recovery accuracy. In recent years, "Hartmann wavefront sensor centroid measurement accuracy optimization method" (patent number CN101055223), "a Hartmann wavefront sensor using time-sharing exposure" (patent publication number CN102607718A) and "a Hartmann wavefront sensor with time-sharing exposure" have been developed successively. However, these methods do not quantitatively consider the influence caused by the intensity distribution of the entrance pupil, and it is difficult to quantify the wavefront recovery. Precision optimization effect.

In the method of the present invention, aiming at the above problems, a Hartmann wavefront restoration method based on the pupil mapping model is proposed. According to the entrance pupil information of the Hartmann wavefront sensor, through appropriate data processing methods, the centroid deviation of the sub-apertures caused by the non-uniformity characteristics of the pupil distribution in time/space domain is extracted, and the sub-aperture with small centroid deviation is selected. The wavefront recovery is completed in the form of a pattern recovery matrix. The method comprehensively considers the non-uniform characteristics of the pupil, and is especially suitable for the Hartmann wavefront detection of pupils with dynamic intensity distribution characteristics. At the same time, it can also provide certain auxiliary functions for the accurate correction of aberrations under the dynamic intensity distribution pupil and the stable decoupling of multiple correctors.

SUMMARY OF THE INVENTION

The technical problem to be solved by the present invention is: when there is spatial/temporal non-uniformity in the pupil intensity distribution of the beam to be measured, the near-field light intensity in the corresponding area of the sub-aperture will affect the sub-spot shape, resulting in the loss of the sub-aperture wavefront restoration information. Extraction error. Aiming at this problem, this paper proposes a wavefront restoration method that quantitatively considers the influence of pupil intensity distribution, reduces the wavefront restoration error as much as possible, and improves the wavefront restoration accuracy.

The technical solution adopted by the present invention to solve the technical problem is: a Hartmann wavefront restoration method based on a pupil mapping model, the method aims at high-precision wavefront restoration under the non-uniform pupil in the space/time domain , through the intensity analysis of the entrance pupil, select the effective sub-aperture for wavefront restoration, reconstruct the mode restoration matrix, and complete the wavefront restoration.

The specific implementation steps are as follows:

Step (1), build a Hartmann wavefront sensor, and obtain the pupil intensity distribution information of the incident beam before wavefront detection. The pupil intensity distribution information can be acquired synchronously with the wavefront detection process of the Hartmann wavefront sensor, or can be obtained in the form of pupil prior information, pre-acquisition or post-processing.

Step (2), using the pupil intensity distribution information of the incident light beam and combining with the structural parameters of the Hartmann wavefront sensor, theoretically calculate the sub-spot image of the pupil distribution under the plane wave phase. Analyze the degree to which the wavefront restoration information of each sub-aperture is affected by the pupil intensity distribution, select the sub-aperture that is less affected by the intensity distribution as the effective sub-aperture, and reconstruct the wavefront restoration matrix;

The wavefront restoration information of each sub-aperture may be the sub-aperture slope, the second-order moment of the sub-wavefront, or the sub-aperture spot inversion information, or the like.

The effective sub-aperture criterion may adopt the theoretical offset or statistical value of information such as the sub-aperture slope/second-order moment, and may also adopt methods such as sub-spot morphological analysis.

Step (3): Incident the beam on the Hartmann wavefront sensor, collect the sub-spot image of the Hartmann wavefront sensor, extract the wavefront restoration information of each sub-aperture, and use the reconstructed wavefront restoration matrix to complete the wavefront restoration . During the extraction of wavefront restoration information for each sub-aperture, further operations such as sub-aperture subtraction threshold, sub-aperture windowing, centroid correction, and slope weighting can be performed in parallel.

The principle of the invention is: obtain the influence of the near-field intensity distribution on the Hartmann sub-spot through the entrance pupil mapping model, select the Hartmann effective sub-aperture accordingly, and use the effective sub-aperture to complete the wavefront restoration.

Compared with the prior art, the present invention has the following advantages: the method comprehensively considers the temporal/spatial non-uniformity of pupil distribution, and is expected to improve the accuracy and stability of Hartmann wavefront restoration under non-uniform pupils. The method can improve the practical ability of the Hartmann wavefront sensor, and make it possible to accurately detect or restore the wavefront under pupil conditions such as irregularities and flickering.

Description of drawings

1 is a working light path diagram of a Hartmann wavefront restoration method based on pupil mapping model of the present invention, wherein 1 is a spectroscope BS, 2 is a microlens array, 3 is a Hartmann detector, and 4 is a light pupil detector;

FIG. 2 is a comparison diagram of the wavefront restoration results of the method involved in the present invention and the traditional method for the non-uniform near-field in the spatial domain;

FIG. 3 is a working flow chart of a Hartmann wavefront restoration method based on a pupil mapping model of the present invention.

Detailed ways

The present invention will be further described below with reference to the accompanying drawings and specific embodiments.

As shown in Figure 2, the specific embodiment of a Hartmann wavefront restoration method based on a pupil mapping model of the present invention is as follows:

Step (1), build a Hartmann wavefront sensor, and collect pupil intensity distribution images synchronously. In this embodiment, the Hartmann wavefront sensor has a total of 76 sub-apertures in a square layout, each sub-aperture has a size of 1 mm×1 mm, and a focal length of 21.7 mm. The entrance pupil is Φ10mm, the intensity is dynamically non-uniform, and the light intensity filling factor F is between 0.2 and 0.8 (the lower the F factor, the more non-uniform the near-field light intensity is). It is intended to detect the first 15th order Zernike mode aberrations.

As shown in FIG. 1 , the Hartmann wavefront sensor includes a microlens array 2 and a Hartmann detector 3 . The beam to be measured is split by the beam splitter BS 1 , a part is focused and imaged on the Hartmann detector 3 by the microlens array 2 , and the other part is incident on the pupil detector 4 . The pupil detector 4 is used to obtain the pupil mapping model, and the Hartmann detector 3 performs wavefront restoration according to the imaging spot array and the pupil mapping model.

Step (2), using the pupil intensity distribution information of the incident light beam and combining with the structural parameters of the Hartmann wavefront sensor, theoretically calculate the sub-spot image of the pupil distribution under the plane wave phase. Analyze the degree to which the slope of each sub-aperture is affected by the pupil intensity distribution, select the sub-aperture that is less affected by the intensity distribution as the effective sub-aperture, and reconstruct the wavefront restoration matrix;

In this embodiment, while extracting the slope of each sub-aperture, the Hartmann wavefront sensor calculates the slope shift of each sub-aperture under the influence of the near field according to the pupil intensity distribution, and selects the sub-aperture whose slope deviates from 0.1 pixel as the effective sub-aperture . The mode restoration matrix is reconstructed according to the effective sub-aperture number.

The slope information of the light spot array obtained by the Hartmann detector is denoted as S, and the slope error matrix obtained according to the pupil mapping model is Se. S and Se are matrices of the same dimension. If abs(Se)>0.1, the slope S of the corresponding serial number is set to zero, and it is considered to be an invalid sub-aperture. Then, the mode restoration matrix G is reconstructed according to the effective sub-aperture number.

Step (3), using the reconstructed wavefront restoration matrix to complete the wavefront restoration. The specific calculation process is as follows: the restoration wavefront W=GS.

In this embodiment, 6000 groups of wavefront restoration results of different near-field distributions under a certain aberration level are counted. The near-field fill factor of the optical field fluctuates between 0.2 and 0.8, with an average F≈0.5, and the input wavefront RMS≈2λ. Statistics show that the wavefront restoration residual RMS ≈ 0.18λ of the Ben Hartmann wavefront sensor in the uniform near field; under the non-uniform near field, the restoration residuals of this method and the traditional method are shown in Figure 2. It can be seen that It can be seen that by selecting the effective sub-aperture, the wavefront restoration accuracy can be improved, and the optimization effect is more obvious when the F factor is low. In the statistical results, there are about 1800 groups of data with F≤0.4, the traditional method has an average restoration residual RMS≈0.50λ, and this method has an average restoration residual RMS≈0.38λ. If combined with slope correction and other measures, the wavefront restoration accuracy is expected to be further improved.

Contents that are not described in detail in the specification of the present invention belong to the prior art known to those skilled in the art.

Claims (5)

1. a Hartmann wavefront restoration method based on pupil mapping model, is characterized in that, realization step is as follows: Step (1), build a Hartmann wavefront sensor, and obtain the pupil intensity distribution information of the incident beam before wavefront detection; Step (2): Using the pupil intensity distribution information of the incident beam, combined with the structural parameters of the Hartmann wavefront sensor, theoretically calculate the sub-spot image of the pupil distribution under the plane wave phase, and analyze the wavefront restoration information of each sub-aperture to receive light The degree of influence of the pupil intensity distribution, select the sub-aperture that is less affected by the intensity distribution as the effective sub-aperture, and reconstruct the wavefront restoration matrix; Step (3): Incident the beam on the Hartmann wavefront sensor, collect the sub-spot image of the Hartmann wavefront sensor, extract the wavefront restoration information of each sub-aperture, and use the reconstructed wavefront restoration matrix to complete the wavefront restoration . 2. a kind of Hartmann wavefront restoration method based on pupil mapping model according to claim 1, is characterized in that: the pupil intensity distribution information described in step (1) can be along with Hartmann wavefront sensor wave The pre-detection process is acquired synchronously, and may also be in the form of pupil prior information, pre-acquisition or post-processing. 3. a kind of Hartmann wavefront restoration method based on pupil mapping model according to claim 1, is characterized in that: the wavefront restoration information of each sub-aperture described in step (2) can be sub-aperture slope, The information can also be inverted for the second moment of the wavefront or the subaperture spot. 4. a kind of Hartmann wavefront restoration method based on pupil mapping model according to claim 1, is characterized in that: the effective sub-aperture criterion described in step (2) can adopt sub-aperture slope/second order moment The theoretical offset or statistical value of the information can also be analyzed by the sub-spot morphological analysis method. 5. a kind of Hartmann wavefront restoration method based on pupil mapping model according to claim 1, is characterized in that: in each sub-aperture wavefront restoration information extraction process described in step (3), can parallel further Operations such as sub-aperture subtraction threshold, sub-aperture windowing, centroid correction, and slope weighting.

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