Infrared material optical uniformity detection method based on model calculation

Abstract

The invention discloses an infrared material optical uniformity detection method based on model calculation. Building a surface shape detection light path on the surface of the oblique incidence flat plate sample by using a spherical interferometer, and adjusting a spherical reflector to make interference fringes sparse; the sample is turned over by 180 degrees, and the surface shape of the other surface of the flat plate sample is measured; the method comprises the following steps: establishing an optical uniformity detection light path on the surface of a normal incidence flat sample by using a spherical interferometer, and adjusting a spherical reflector to make interference fringes sparse; the flat plate sample is moved out of the interference light path, and cavity measurement results of the interferometer and the spherical reflector are measured; the method comprises the following steps of: establishing a ray tracing model of a normal incidence flat plate sample of the spherical interferometer, representing the optical uniformity of the flat plate sample by using a polynomial, taking a polynomial coefficient and a distance from the flat plate sample to the interferometer as variables of iterative calculation, and taking wavefront data measured by the normal incidence flat plate sample of the spherical interferometer as a target value of the iterative calculation; and iteratively calculating to obtain a mathematical expression of the optical uniformity of the flat plate sample.

Description

Technical Field

[0001] The present application relates to the technical field of optical uniformity of infrared materials, and in particular to a method for detecting optical uniformity of infrared materials based on model calculation. Background Art

[0002] Large-aperture infrared materials are increasingly used in space optical remote sensors, and their optical uniformity is an important factor affecting the imaging quality of optical remote sensors. Using highly uniform infrared materials or compensating for the influence of infrared material optical uniformity through the optimization design of the optical system is an important means to ensure the quality of remote sensors. Therefore, high-precision detection of the optical uniformity of large-aperture infrared materials is very important.

[0003] At present, the main methods used for optical uniformity detection of optical materials at home and abroad include the mounting plate method, the four-step interference method, the parallel plate method, etc. Among them, the mounting plate method is suitable for the optical uniformity measurement of small-caliber materials, and this method cannot correct the systematic error of the measuring equipment. The method of measuring the optical uniformity of parallel plates using wavelength-tuned phase-shifting interferometer is only applicable to parallel plate samples of visible light materials, and cannot detect flat materials with wedge angles. In addition, all of the above methods require a plane wave interferometer with an aperture equivalent to that of the flat sample. Due to the lack of large-aperture infrared plane interferometers at home and abroad, the uniformity measurement method of large-aperture infrared materials is often to add an additional beam expansion system to the test optical path of the spherical wave infrared interferometer to form a large-aperture collimated wavefront detection optical path. The additional beam expansion system greatly increases the detection cost, and the beam expansion system needs to be adjusted and calibrated with high precision, making the detection system more complicated. Another optical uniformity detection optical path is to use non-collimated light interferometry. The spherical wave is directly output through the test arm of the infrared spherical wave interferometer, passes through the flat sample, and then returns to the original optical path after passing through the spherical reflector to form interference. Although this method can obtain the influence of the optical uniformity of the flat sample on the spherical wave, it does not consider the propagation characteristics of the spherical wave in the flat sample. In addition, the surface shape of the flat sample will be coupled with the refractive index distribution, and an additional large interferometer is required to detect the surface shape of the sample, which increases the detection cost. Summary of the invention

[0004] The present application provides a method for detecting optical uniformity of infrared materials based on model calculation, which is implemented by adopting non-collimated light interferometry measurement technology, ray tracing model calculation technology and iterative optimization calculation technology. It can be used for uniformity detection of large-aperture infrared materials and has important applications in the optimization design and detection of infrared space optical remote sensors.

[0005] In a first aspect, a method for detecting optical uniformity of infrared materials based on model calculation is provided, comprising:

[0006] Build a uniformity detection platform for testing, including front and back surface shape detection, transmitted wavefront detection, and interferometric cavity detection of flat sample materials;

[0007] Zemax software was used to establish a ray tracing model for testing the transmitted wavefront of a flat sample, and simulation was performed based on the uniformity test results.

[0008] According to the interference cavity detection results and the ray tracing model simulation results, the material optical uniformity distribution H of the flat sample is iteratively solved.

[0009] In combination with the first aspect, in certain implementations of the first aspect, the uniformity detection platform includes a spherical wave interferometer, a flat sample, and a standard spherical reflector;

[0010] In the oblique incident detection optical path of the flat sample surface, the light emitted by the spherical wave interferometer is reflected by the surface of the flat sample and then incident on the standard spherical reflector, and then reflected by the standard spherical reflector and then incident on the surface of the flat sample and returns to the spherical wave interferometer;

[0011] In the detection optical path of the interference cavity, the center of the reflector coincides with the focus of the interferometer;

[0012] In the transmission wavefront detection optical path of the flat sample, the light emitted by the spherical wave interferometer passes through the flat sample and enters the standard spherical reflector, passes through the flat sample again after being reflected by the standard spherical reflector, and returns to the spherical wave interferometer;

[0013] In combination with the first aspect, in some implementations of the first aspect, the uniformity detection includes:

[0014] Place the normal direction of the flat sample surface at an angle θ to the optical axis direction of the spherical wave interferometer, and the center of the standard spherical reflector coincides with the focus of the interferometer; first perform a surface shape test on the front surface A of the flat sample to obtain a measurement result W1; then flip the flat sample 180°, perform a surface shape test on its rear surface B, and obtain a measurement result W2;

[0015] Remove the flat sample and build the detection optical path of the interference cavity; overlap the center of the standard spherical reflector with the focus of the interferometer, perform interference cavity detection, and obtain the measurement result W3;

[0016] Place the flat sample in the detection light path, build the transmission wavefront detection light path of the flat sample, measure the transmission wavefront of the flat sample, and obtain the measurement result W t .

[0017] In combination with the first aspect, in some implementations of the first aspect, the angle θ is 30° to 60°.

[0018] In combination with the first aspect, in certain implementations of the first aspect, in the ray tracing model, the front surface shape data W of the flat sample A for:

[0019]

[0020] In the ray tracing model, the rear surface shape data W of the flat sample is B for:

[0021]

[0022] Wherein, d represents the distance from the measured surface of the flat sample to the focus of the interferometer 1, θ represents the normalized coordinates of the flat sample x and y represent the measurement results.

[0023] In combination with the first aspect, in certain implementations of the first aspect, the material optical uniformity distribution H of the flat sample is characterized by a Zernike polynomial as follows: Where Z i (x,y) represents the i-th Zernike polynomial, A i Represents the coefficients of the Zernike polynomial.

[0024] In combination with the first aspect, in certain implementations of the first aspect, iteratively solving the material optical uniformity distribution H of the flat sample includes:

[0025] Optical uniformity distribution of materials according to flat sample Calculated by the ray tracing model in Zemax Figure 2 The transmitted wavefront of the flat sample under the optical path shown in (d) is W m , by changing The polynomial coefficient A i , to change the ray tracing model result W m , when the ray tracing model result W m The transmitted wavefront detection result W of the flat sample t When the difference is less than the set value ε, the loop iteration ends.

[0026] In combination with the first aspect, in some implementations of the first aspect, a parallel gradient descent algorithm is used to iteratively optimize each coefficient at the same time; i The iterative process satisfies:

[0027] A (n+1) (n+1,i)=A (n) (n,i)-α·δ(J)·δ(A)

[0028] δ(J)=STD(Wm(A (n) +δ(A))-Wt )-STD(Wm(A (n) -δ(A))-W t )

[0029] α is the iteration coefficient; δ(A) is A i The random variable of the coefficient is a random number between 0 and 1; STD means the root mean square value of the wavefront data.

[0030] In combination with the first aspect, in some implementations of the first aspect, the value of α is 0.1 to 0.2.

[0031] In conjunction with the first aspect, in certain implementations of the first aspect, the optical uniformity of the material of the flat sample meets the requirements, including:

[0032] The absolute value of H is less than a first preset threshold;

[0033] Z4~Z 10 The absolute values ​​of the coefficients are all less than the second preset threshold.

[0034] Compared with the prior art, the solution provided by this application includes at least the following beneficial technical effects:

[0035] The present invention uses non-collimated light interferometry to measure the optical uniformity of infrared materials, obtains the surface shape of the material to be measured by oblique incidence of non-collimated light, and then obtains the mathematical expression of the optical uniformity of the material by iterative calculation. The problem of difficulty in detecting the optical uniformity of large-aperture infrared materials and dependence on large-aperture plane interferometers is solved, and the problem of coupling between the surface shape error of the material and the optical uniformity when non-collimated light is used to detect the optical uniformity of the material is solved. The present invention is universal for uniformity detection of flat plate materials with different apertures and different wedge angles, and has the advantages of high precision, simple detection optical path, and low detection cost in the detection of optical uniformity of large-aperture infrared materials. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 Flow chart of the method of the present invention.

[0037] Figure 2 It is a schematic diagram for implementing the method of the present invention.

[0038] Figure 3 It is a schematic diagram of the calculation results of the optical uniformity of the material of the present invention. DETAILED DESCRIPTION

[0039] The present application is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0040] like Figure 1 As shown, the present invention provides an infrared material optical uniformity detection method based on model calculation.

[0041] Step 1: Build a uniformity detection platform for detection, including front and rear surface shape detection of the flat sample, transmitted wavefront detection, and interference cavity detection.

[0042] like Figure 2 As shown, the present invention adopts a uniformity detection platform including a spherical wave interferometer 1, a flat sample 2, and a standard spherical reflector 3. In the oblique incident detection optical path of the flat sample surface shape, the light emitted by the spherical wave interferometer 1 is reflected by the surface of the flat sample 2 and then incident on the standard spherical reflector 3, and then reflected by the standard spherical reflector 3 and then incident on the surface of the flat sample 2, and then returns to the spherical wave interferometer 1. In the detection optical path of the interference cavity, the center of the reflector 3 coincides with the focus of the interferometer 1. In the transmission wavefront detection optical path of the flat sample 2, the light emitted by the spherical wave interferometer 1 passes through the flat sample 2 and enters the standard spherical reflector 3, and then reflects by the standard spherical reflector 3 and then passes through the flat sample 2 again, and returns to the spherical wave interferometer 1.

[0043] Step 1.1, build an oblique incident detection optical path for the surface shape of the flat sample, and perform surface shape detection on the front and back surfaces of the flat sample 2. Place the normal direction of the surface of the flat sample 2 at an angle θ (30° to 60°) to the optical axis direction of the spherical wave interferometer 1, and the center of the reflector 3 coincides with the focus of the interferometer 1. First, perform surface shape detection on the front surface A of the flat sample 2 to obtain the measurement result W1; then flip the flat sample 2 180°, perform surface shape detection on its rear surface B, and obtain the measurement result W2.

[0044] Step 1.2, remove the flat sample 2, build the detection optical path of the interference cavity, make the center of the reflector 3 coincide with the focus of the interferometer 1, perform interference cavity detection, and obtain the measurement result W3.

[0045] Step 1.3, place the flat sample 2 in the detection light path, build the transmission wavefront detection light path of the flat sample 2, measure the transmission wavefront of the flat sample 2, and obtain the measurement result W t .

[0046] Step 2: Use Zemax software to establish a ray tracing model for detecting the transmitted wavefront of the flat sample 2, such as Figure 2 As shown in (d), simulation is performed based on the uniformity test results.

[0047] In the ray tracing model, the front surface shape data W of the flat sample 2 is A for:

[0048]

[0049] In the ray tracing model, the rear surface shape data W of the flat sample 2 is B for:

[0050]

[0051] Wherein, d represents the distance from the measured surface of the flat sample 2 to the focus of the interferometer 1, and x and y represent the normalized coordinates of the measurement results.

[0052] Step 3, the material optical uniformity distribution H of the flat sample 2 is characterized by the Zernike polynomial:

[0053]

[0054] Where Z i (x,y) represents the i-th Zernike polynomial, A i Represents the coefficients of the Zernike polynomials, including astigmatism, coma, trefoil, and spherical aberration terms.

[0055] Step 4: Based on the interference cavity detection results and the ray tracing model simulation results, the material optical uniformity distribution of the flat sample 2 is analyzed. Perform iterative solution.

[0056] According to the material optical uniformity distribution of flat sample 2 Calculated by the ray tracing model in Zemax Figure 2 (d) The transmitted wavefront of the flat sample 2 under the optical path shown is W m , by changing The polynomial coefficient A i , to change the ray tracing model result W m , when the ray tracing model result W m The transmission wavefront detection result W of flat sample 2 t When the difference is less than the set value ε, the loop iteration ends.

[0057] The calculation process is as follows Figure 1 As shown. The material optical uniformity distribution expression of flat sample 2 is The polynomial coefficient A i As a variable for iterative calculation. In one embodiment, a parallel gradient descent algorithm is used to iteratively optimize each coefficient at the same time. i The iterative process satisfies:

[0058] A (n+1) (n+1,i)=A (n) (n,i)-α·δ(J)·δ(A)

[0059] δ(J)=STD(Wm(A (n) +δ(A))-W t )-STD(Wm(A (n) -δ(A))-Wt )

[0060] Wherein, α is the iteration coefficient, and its value is, for example, 0.1 to 0.2; δ(A) is A i The random variable of the coefficient is a random number between 0 and 1; STD means the root mean square value of the wavefront data.

[0061] When the ray tracing model result W m The transmission wavefront detection result W of flat sample 2 t When the difference is less than the set value ε, the iteration ends. The final calculated result of the optical uniformity of the material of the flat sample 2 is H = h4Z4 + h5Z5 + h6Z6 + h7Z7 + h8Z8 + h9Z9 + h 10 Z 10 Z4 represents the defocus term, Z5 represents the 0° phase divergence term, Z6 represents the 90° phase divergence term, Z7 represents the coma term in the X direction, Z8 represents the coma term in the Y direction, Z9 represents the trefoil term, and Z 10 represents the spherical aberration term.

[0062] Material optical uniformity distribution H in Z4~Z 10 The coefficient reflects the material optical uniformity of the flat sample 2. The material optical uniformity of the flat sample 2 meets the requirements, including: the absolute value of H is less than the first preset threshold; Z4~Z 10 The absolute values ​​of the coefficients are all less than the second preset threshold.

[0063] In one embodiment, ε is 0.02, and the calculated result of the material optical uniformity of the flat sample 2 is H=-2.57×10 -5 Z4 -8.29×10 -5 Z5+9.82×10 -5 Z6 -1.19×10 -5 Z7+1.79×10 -5 Z8-2.2×10 - 5 Z9 -2.76×10 -5 Z 10 , the optical uniformity distribution is as follows Figure 3 shown.

[0064] In summary, the solution provided by the present invention overcomes the shortcoming that non-collimated light interference detection cannot obtain the optical uniformity distribution of flat sample with high precision. The method provided by the present invention uses non-collimated light to obliquely incident on the flat sample to perform interference detection on the surface shape of the flat sample, and measures the optical uniformity of the flat sample when non-collimated light is incident on the flat sample normally. Through ray tracing and parallel gradient descent iterative calculation method, the mathematical expression of the optical uniformity of the flat sample is obtained.

[0065] Although the present invention is disclosed as above in the form of a preferred embodiment, it is not intended to limit the present invention. Any person skilled in the art may make possible changes and modifications without departing from the spirit and scope of the present invention. Therefore, the scope of protection of the present invention shall be based on the scope defined by the claims of the present invention.

Claims

1. A method for detecting optical uniformity of infrared materials based on model calculation, characterized in that: include: Build a uniformity detection platform for testing, including front and back surface shape detection, transmitted wavefront detection, and interferometric cavity detection of flat sample materials; Zemax software was used to establish a ray tracing model for testing the transmitted wavefront of a flat sample, and simulation was performed based on the uniformity test results. According to the interference cavity detection results and the ray tracing model simulation results, the material optical uniformity distribution H of the flat sample is iteratively solved.

2. The method according to claim 1, characterized in that The uniformity detection platform includes a spherical wave interferometer, a flat sample, and a standard spherical reflector; In the oblique incident detection optical path of the flat sample surface, the light emitted by the spherical wave interferometer is reflected by the surface of the flat sample and then incident on the standard spherical reflector, and then reflected by the standard spherical reflector and then incident on the surface of the flat sample and returns to the spherical wave interferometer; In the detection optical path of the interference cavity, the center of the reflector coincides with the focus of the interferometer; In the transmission wavefront detection optical path of the flat sample, the light emitted by the spherical wave interferometer passes through the flat sample and enters the standard spherical reflector. After being reflected by the standard spherical reflector, it passes through the flat sample again and returns to the spherical wave interferometer.

3. The method according to claim 1, characterized in that The uniformity detection includes: Place the normal direction of the flat sample surface at an angle θ to the optical axis direction of the spherical wave interferometer, and the center of the standard spherical reflector coincides with the focus of the interferometer; first perform a surface shape test on the front surface A of the flat sample to obtain a measurement result W1; then flip the flat sample 180°, perform a surface shape test on its rear surface B, and obtain a measurement result W2; Remove the flat sample and build the detection optical path of the interference cavity; overlap the center of the standard spherical reflector with the focus of the interferometer, perform interference cavity detection, and obtain the measurement result W3; Place the flat sample in the detection light path, build the transmission wavefront detection light path of the flat sample, measure the transmission wavefront of the flat sample, and obtain the measurement result W t .

4. The method according to claim 3, characterized in that The angle θ is 30° to 60°.

5. The method according to claim 1, characterized in that In the ray tracing model, the front surface shape data W of the flat sample A for: In the ray tracing model, the rear surface shape data W of the flat sample is B for: Wherein, d represents the distance from the measured surface of the flat sample to the focus of the interferometer 1, θ represents the normalized coordinates of the flat sample x and y represent the measurement results.

6. The method according to claim 1, characterized in that The material optical uniformity distribution H of the flat sample is characterized by the Zernike polynomial as follows: Where Z i (x,y) represents the i-th Zernike polynomial, A i Represents the coefficients of the Zernike polynomial.

7. The method according to claim 6, characterized in that Iterative solution of the material optical uniformity distribution H of the flat sample includes: Optical uniformity distribution of materials according to flat sample The ray tracing model in Zemax calculates that the transmitted wavefront of the flat sample under the optical path shown in Figure 2(d) is W m , by changing The polynomial coefficient A i , to change the ray tracing model result W m , when the ray tracing model result W m The transmitted wavefront detection result W of the flat sample t When the difference is less than the set value ε, the loop iteration ends.

8. The method according to claim 7, characterized in that A parallel gradient descent algorithm is used to iteratively optimize each coefficient at the same time; A i The iterative process satisfies: A (n+1) (n+1,i)=A (n) (n,i)-α·δ(J)·δ(A) δ(J)=STD(Wm(A (n) +δ(A))-W t )-STD(Wm(A (n) -δ(A))-W t ) α is the iteration coefficient; δ(A) is A i The random variable of the coefficient is a random number between 0 and 1; STD means the root mean square value of the wavefront data.

9. The method according to claim 8, characterized in that The value of α is 0.1~0.

2.

10. The method according to claim 7, characterized in that The material optical homogeneity of the flat sample meets the requirements, including: The absolute value of H is less than a first preset threshold; Z4~Z 10 The absolute values ​​of the coefficients are all less than the second preset threshold.

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