Primary and secondary lens calibration method based on neural network algorithm

A technology of neural network algorithm and calibration method, which is applied in the field of primary and secondary mirror installation and adjustment of off-axis reflective systems, can solve the problems of unproven robustness of correction models and low universality, and achieves wide applicability and improved installation. Adjustable efficiency and high reusability

Active Publication Date: 2019-08-30
INST OF OPTICS & ELECTRONICS - CHINESE ACAD OF SCI
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Problems solved by technology

It can be used not only to assist the design of decentered tilted optical systems, but also to analyze misaligned optical systems, but its universality is low, and the robustness of the correction model needs to be demonstrated

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  • Primary and secondary lens calibration method based on neural network algorithm
  • Primary and secondary lens calibration method based on neural network algorithm
  • Primary and secondary lens calibration method based on neural network algorithm

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Embodiment Construction

[0040] The scheme of the present invention will be further described below in conjunction with the accompanying drawings and specific implementation steps.

[0041] like figure 1 As shown in the flow chart on the right, the primary and secondary mirror calibration method based on the neural network algorithm includes the following steps:

[0042] Step 1 Model establishment:

[0043] First, input the structural parameters of the off-axis optical system to be tested in the optical simulation software, and establish the optical model;

[0044] Step 2 Acquisition of training samples:

[0045] First record the first 37 Zernike coefficients Z without adding any alignment error 0 ,As follows:

[0046]

[0047] where θ 1 , θ 2 , θ 3 Indicates the different viewing angles of the telescope system;

[0048] like figure 2 As shown, the misalignment of the two lenses mainly includes the off-axis error d on the X and Y axes r , the defocus error d in the Z-axis direction r (b...

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Abstract

The invention discloses a primary and secondary lens calibration method based on a neural network algorithm. The method comprises the steps of firstly, establishing a primary and secondary lens imbalance model through simulation software, and then obtainining a corresponding Zernike polynomial coefficient through the randomly-added imbalance; secondly, combining the offset and a corresponding Zernike polynomial coefficient into a data set, and repeating the above steps to obtain a sufficient data set; then, using the data set as a training sample to train the neural network; and finally, inputting the Zernike polynomial coefficient representing the to-be-tested system into the trained neural network, and further obtaining the misalignment of the primary and secondary lens alignment. The method is suitable for calculating the alignment offset of various types of lenses, can effectively improve the installation and adjustment efficiency of the optical lens of a telescope system, and is suitable for the real-time calibration of the primary and secondary lenses.

Description

technical field [0001] The invention belongs to the field of adjusting primary and secondary mirrors of an off-axis reflective system, and in particular relates to a primary and secondary mirror calibration method based on a neural network algorithm. Background technique [0002] The off-axis reflective optical system has the advantages of no obstruction, large field of view, compact structure, and no chromatic aberration. It has been widely used in 3D surveying and mapping, space remote sensing, astronomical observation, and multispectral thermal imaging. At present, the calculation speed of the alignment error of the primary and secondary mirrors of the off-axis reflective system is not fast. Therefore, how to quickly and accurately obtain the misalignment of the primary and secondary mirrors of the off-axis reflective system is of great significance for real-time adjustment. [0003] The adjustment of the primary and secondary mirrors of the early telescope system mainly ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/16G06F17/50G06N3/04G06N3/06G06N3/08
CPCG06N3/061G06N3/08G06F17/16G06F30/20G06N3/045
Inventor 刘柱彭起任戈谭玉凤
Owner INST OF OPTICS & ELECTRONICS - CHINESE ACAD OF SCI
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