Pyramid wavefront sensor and target wavefront detection method

Abstract

The present invention provides a pyramid wavefront sensor and a target wavefront detection method, wherein the pyramid wavefront sensor includes a first converging lens, a field stop, a corner cone prism, a second converging lens and a detection camera arranged in sequence along the propagation direction of a light beam, the vertex of the corner cone prism is located at the focus of the first converging lens, and the detection plane of the detection camera is conjugate to the plane where the vertex of the corner cone prism is located; a microlens array is arranged between the second converging lens and the detection camera, and the microlens array is used to effectively separate the target signal on the detection camera from the skylight background signal. The present invention combines the corner cone prism and the microlens array to achieve effective separation of the skylight background signal and the target signal, and cooperates with the skylight elimination algorithm to calculate and remove the skylight value of each sub-aperture, extract the effective information of the target, and is more suitable for the detection of weak targets, thereby effectively realizing the application of the pyramid wavefront sensor in the daytime natural guide star adaptive optical system.

Description

Technical Field

[0001] The present invention relates to the field of wavefront sensing technology, and in particular to a pyramid wavefront sensor and a target wavefront detection method used in a daytime natural guide adaptive optical system. Background Art

[0002] Adaptive optics is an optical technology that improves the quality of optical imaging by correcting wavefront errors. As an important front-end link in adaptive optics, wavefront sensing technology mainly measures the wavefront aberration caused by atmospheric turbulence and other factors in real time for the adaptive optical system, and provides wavefront signals for the wavefront processor. The pyramid wavefront sensor is a new wavefront sensing technology first proposed by astronomer Roberto Ragazzoni in 1996. It mainly realizes wavefront detection in adaptive optical systems and has been applied to the adaptive optical systems of many world-class ground-based large-aperture astronomical telescopes. The optical structure of the pyramid wavefront sensor is as follows: Figure 1 shown.

[0003] In astronomical detection, the pyramid wavefront sensor in the adaptive optical system of ground-based large-aperture telescopes often works at night and uses natural guide stars as the wavefront reference light source. When working during the day, the optical structure of the pyramid wavefront sensor used in the daytime natural guide star adaptive optical system is as follows: Figure 2 As shown, the obtained target and background mixed signal image is as follows Figure 3 As shown, let the incident signal be the target signal only, and the target signal image is as follows Figure 4 As shown. Figure 3 and Figure 4 It can be clearly seen from the comparison that the relatively weaker target signal in the pupil image is covered by the strong sky light background signal, and the effective information of the target cannot be extracted, which greatly limits the application of pyramid wavefront sensors in daytime natural guide adaptive optics. Summary of the invention

[0004] The purpose of the present invention is to overcome the defects of the existing technology and propose a pyramid wavefront sensor and a target wavefront detection method for use in a daytime natural guide star adaptive optical system, which combines a corner cone prism and a microlens array to achieve effective separation of sky light background signals and target signals, and uses a sky light elimination algorithm to extract effective target signals, thereby realizing the application of the pyramid wavefront sensor in the daytime natural guide star adaptive optical system.

[0005] To achieve the above object, the present invention adopts the following specific technical solutions:

[0006] The pyramid wavefront sensor provided by the present invention comprises a first converging lens, a field aperture, a corner cube prism, a second converging lens and a detection camera which are sequentially arranged along the propagation direction of a light beam, the vertex of the corner cube prism is located at the focus of the first converging lens, and the detection plane of the detection camera is conjugate to the plane where the vertex of the corner cube prism is located; a microlens array is arranged between the second converging lens and the detection camera, and the microlens array is used to effectively separate the target signal on the detection camera from the skylight background signal.

[0007] Preferably, the detection camera forms different sub-pupil images corresponding to each face of the corner cube prism, and the number of sub-apertures divided by each sub-pupil image is the same as the number of microlenses in the microlens array occupied by the sub-apertures.

[0008] Preferably, the skylight background signal appears as a fan-shaped image on each sub-aperture, and the target signal is gathered at the vertex position of the fan-shaped image.

[0009] The target wavefront detection method using the pyramid wavefront sensor provided by the present invention comprises the following steps:

[0010] S1. Using a skylight elimination algorithm to remove the skylight value of each sub-aperture in each sub-pupil image formed by the detection camera, extracting effective target signals;

[0011] S2. Calculate the target's wavefront information based on the effective target signal.

[0012] Preferably, step S1 includes the following sub-steps:

[0013] S11, extracting all pixel points containing target signals and skylight background signals in the fan-shaped area of ​​each sub-aperture, and determining the coordinates of the pixel point with the maximum grayscale value among all the pixel points;

[0014] S12, removing the pixel coordinates of the maximum gray value pixel and the pixels within a predetermined range around the pixel coordinates of the maximum gray value, leaving the remaining pixels;

[0015] S13, calculate the average gray value of the remaining pixels With standard deviation σ i (x, y); where i represents the number of the sub-pupil image, and (x, y) represents the coordinates of the sub-aperture;

[0016] S14, based on the average grayscale values ​​of the remaining pixels With standard deviation σ i (x, y), calculate the skylight value B for each sub-aperture i (x, y), the calculation formula is as follows:

[0017]

[0018] Where K represents the coefficient;

[0019] S15. Subtract the corresponding skylight value B from each sub-aperture i (x, y), and extract the effective target signals I1, I2, I3, and I4 of each sub-pupil image; among them, I1, I2, I3, and I4 correspond to the upper left sub-pupil image, upper right sub-pupil image, lower right sub-pupil image, and lower left sub-pupil image on the detection camera, respectively.

[0020] Preferably, in step S2, the target wavefront information S is calculated according to the effective target signals I1, I2, I3, I4 of each sub-pupil image. x , and S y , the calculation formula is as follows:

[0021]

[0022]

[0023] Compared with the prior art, the present invention can achieve the following technical effects:

[0024] 1. The present invention combines a corner cube prism with a microlens array to achieve effective separation of skylight background signals and target signals, and then uses a skylight elimination algorithm to calculate and remove the skylight value of each sub-aperture in each sub-pupil image to extract effective information of the target. Compared with the daytime natural guide adaptive optics system that only uses a corner cube prism, the present invention is more suitable for weak target detection under low signal-to-noise ratio conditions, and can provide better detection effects under the same signal-to-noise ratio, thereby effectively realizing the application of pyramid wavefront sensors in daytime natural guide adaptive optics systems.

[0025] 2. Compared with the traditional threshold method, the skylight removal algorithm can better cope with the uneven skylight background during the day.

[0026] 3. Compared with the Hartmann wavefront sensor used in the daytime natural guide adaptive optics system, the present invention can provide higher sensitivity and a sampling rate that can be adjusted in real time. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 Schematic diagram of the optical path structure of a traditional pyramid wavefront sensor;

[0028] Figure 2 Schematic diagram of the optical path structure of the traditional pyramid wavefront sensor in the daytime natural guide adaptive optics system;

[0029] Figure 3 This is the mixed signal image of the target and background obtained by the traditional pyramid wavefront sensor under daytime conditions;

[0030] Figure 4This is the target signal image obtained by the traditional pyramid wavefront sensor under daytime conditions;

[0031] Figure 5 A schematic diagram of the optical path structure of a pyramid wavefront sensor according to an embodiment of the present invention;

[0032] Figure 6 A target and background mixed signal image obtained by the pyramid wavefront sensor provided by an embodiment of the present invention under daytime conditions;

[0033] Figure 7 A target signal image obtained by the pyramid wavefront sensor provided by an embodiment of the present invention under daytime conditions;

[0034] Figure 8 This is effective target information extracted based on a skylight elimination algorithm in a target wavefront detection method provided according to an embodiment of the present invention.

[0035] The reference numerals include: 1-first converging lens, 2-field stop, 3-corner cone, 4-second converging lens, 5-microlens array, 6-detection camera, 7-sub-pupil image, 8-sub-aperture. DETAILED DESCRIPTION

[0036] Hereinafter, embodiments of the present invention will be described with reference to the accompanying drawings. In the following description, the same modules are represented by the same reference numerals. In the case of the same reference numerals, their names and functions are also the same. Therefore, the detailed description thereof will not be repeated.

[0037] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and do not constitute a limitation of the present invention.

[0038] Figure 5 The optical path structure of the pyramid wavefront sensor provided according to an embodiment of the present invention is shown.

[0039] like Figure 5 As shown, the pyramid wavefront sensor provided by the embodiment of the present invention includes a first converging lens 1, a field aperture 2, a corner cube prism 3, a second converging lens 4, a microlens array 5 and a detection camera 6 which are arranged in sequence along the propagation direction of the light beam. The vertex of the corner cube prism 3 is located at the focus of the first converging lens 1, and the detection plane of the detection camera 6 is conjugate to the plane where the vertex of the corner cube prism 3 is located, so that the detection plane of the detection camera 6 and the plane where the vertex of the corner cube prism 3 is located form a 4f optical system, and the field aperture 2 is arranged in front of the vertex of the corner cube prism 3.

[0040] The first converging lens 1 receives the incident total signal including the target signal and the skylight background signal. After passing through the field aperture 2 to reduce the influence of the skylight background, the signal passes through the four surfaces of the corner cube prism 3 and the refraction of the second converging lens 4, and then passes through the microlens array 5, and is finally imaged on the detection camera 6, presenting as four sub-pupil images 7. Each sub-pupil image 7 is divided into a plurality of sub-apertures 8. The number of sub-apertures 8 divided by each sub-pupil image 7 is the same as the number of microlenses in the microlens array 5 occupied by each sub-beam refracted by the corner cube prism 3.

[0041] The field of view aperture 2 can limit the field of view of the skylight background and prevent excess skylight background from entering the pyramid wavefront sensor. The size of the field of view aperture 2 can be adjusted to ensure that the skylight background signals in each sub-aperture 8 do not overlap.

[0042] The microlens array 5 is used to effectively separate the target signal from the skylight background signal on the detection camera 6. In each sub-aperture 8, the skylight background signal is presented as a fan-shaped image, and the target signal is gathered at the vertex position of the fan-shaped image, so that the target light and the skylight background signal are separated on the detection camera 6 through the microlens array 5. From the sub-pupil image 7, the target signal is gathered into a point array image, while the skylight background signal is presented as a quarter fan-shaped array image.

[0043] After passing through the corner cube prism 3, the incident mixed light (i.e., the target light and the background light) is divided into four sub-beams and forms four sub-pupil images (circular). The skylight background signal and the target signal overlap. After passing through the microlens array 5, the target signal becomes a point array pattern and the skylight background signal becomes a fan-shaped array pattern, thereby achieving effective separation of the target signal and the skylight background signal.

[0044] Since the target light is a point light source and the sky light background is a surface light source, the target signal is gathered into a point array image and the sky light background signal is a fan-shaped array image.

[0045] The target and background mixed signal image obtained by the pyramid wavefront sensor provided by the embodiment of the present invention is as follows: Figure 6 As shown, let the incident signal be only the target signal, and the target signal image is as follows Figure 7 As shown. Figure 6 and Figure 7 It can be seen from the comparison that after the pyramid wavefront sensor of the embodiment of the present invention, the target signal is gathered into a point array image, while the skylight background signal is presented as a quarter fan-shaped array image, and the target signal can be clearly distinguished from the skylight background signal.

[0046] The above content describes in detail the structure and working principle of the pyramid wavefront sensor provided by the embodiment of the present invention. Corresponding to the pyramid wavefront sensor, the embodiment of the present invention also provides a target wavefront detection method using the pyramid wavefront sensor.

[0047] The target wavefront detection method provided by the embodiment of the present invention comprises the following steps:

[0048] S1. Calculate and remove the skylight value of each sub-aperture in each sub-pupil image formed by the detection camera using a skylight elimination algorithm to extract effective target signals.

[0049] Step S1 includes the following sub-steps:

[0050] S11, extracting all pixel points containing target signals and skylight background signals in a quarter-sector region of each sub-aperture, and determining the coordinates of the pixel point with the maximum grayscale value among all the pixel points.

[0051] S12, removing the pixel coordinates of the maximum gray value pixel and the pixels within a predetermined range around the pixel coordinates of the maximum gray value, leaving the remaining pixels.

[0052] For example, it is determined that 5*5 pixel points around the coordinates of the pixel point with the maximum gray value belong to the target signal, and the predetermined range can be specifically determined according to the optical path structure of the pyramid wavefront sensor.

[0053] S13, calculate the average gray value of the remaining pixels With standard deviation σ i (x, y); where i represents the serial number of the sub-pupil image and (x, y) represents the coordinates of the sub-aperture.

[0054] Among all the pixels, after removing the pixel coordinates of the maximum grayscale value and the pixel coordinates of the maximum grayscale value, calculate the average grayscale value of the remaining pixels With standard deviation σ i (x, y).

[0055] S14, based on the average grayscale values ​​of the remaining pixels With standard deviation σ i (x, y), calculate the skylight value B for each sub-aperture i (x, y), the calculation formula is as follows:

[0056]

[0057] Here, K represents the coefficient, which is adjusted according to the turbulence conditions.

[0058] According to step S14, the intensity distribution of skylight values ​​is obtained.

[0059] S15. Subtract the corresponding skylight value B from each sub-aperture i(x, y), and extract the effective target signals I1, I2, I3, and I4 of each sub-pupil image; among them, I1, I2, I3, and I4 correspond to the upper left sub-pupil image, upper right sub-pupil image, lower right sub-pupil image, and lower left sub-pupil image on the detection camera, respectively.

[0060] First, subtract the corresponding skylight value B from the subaperture with coordinates (x, y) i (x, y), then x = x + 1; y = y + 1, subtract the corresponding skylight value B from the sub-aperture with coordinates (x + 1, y + 1) i (x, y), until the skylight background signal is eliminated for all sub-apertures, the effective target signals I1, I2, I3, and I4 of the four sub-pupil images processed by the skylight elimination algorithm can be extracted, as shown in the attached figure. Figure 8 shown.

[0061] S2. Calculate the target's wavefront information based on the effective target signal.

[0062] The target wavefront information S is calculated based on the effective target signals I1, I2, I3, and I4 of each sub-pupil image. x , and S y , the calculation formula is as follows:

[0063]

[0064]

[0065] The present invention combines a corner cone prism and a microlens array, and cooperates with a skylight elimination algorithm to realize the pyramid wavefront sensing technology of daytime natural guide star adaptive optics, which can detect and correct weak targets under strong background conditions during the day. Compared with the traditional threshold method, the skylight elimination algorithm can better cope with the situation of uneven skylight background during the day. Compared with the Hartmann wavefront sensor used in the daytime natural guide star adaptive optics system, the target wavefront detection method provided by the present invention can provide higher sensitivity and real-time adjustable adoption rate. For the daytime natural guide star adaptive optics system that only uses corner cone prisms, the pyramid wavefront sensor provided by the present invention can be used under lower signal-to-noise ratio conditions, and provide better detection effects under the same signal-to-noise ratio.

[0066] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0067] Although the embodiments of the present invention have been shown and described above, it is to be understood that the above embodiments are exemplary and are not to be construed as limitations of the present invention. A person skilled in the art may change, modify, replace and vary the above embodiments within the scope of the present invention.

[0068] The above specific implementations of the present invention do not constitute a limitation on the protection scope of the present invention. Any other corresponding changes and modifications made based on the technical concept of the present invention should be included in the protection scope of the claims of the present invention.

Claims

1. A pyramid wavefront sensor, comprising a first converging lens, a field stop, a corner cube prism, a second converging lens and a detection camera arranged in sequence along a light beam propagation direction, wherein the vertex of the corner cube prism is located at the focus of the first converging lens, and the detection plane of the detection camera is conjugate to the plane where the vertex of the corner cube prism is located; characterized in that: A microlens array is arranged between the second converging lens and the detection camera, and the microlens array is used to effectively separate the target signal on the detection camera from the skylight background signal.

2. The pyramid wavefront sensor according to claim 1, characterized in that: The detection camera forms different sub-pupil images corresponding to each face of the corner cube prism, and the number of sub-apertures divided by each sub-pupil image is the same as the number of microlenses in the microlens array occupied by the sub-apertures.

3. The pyramid wavefront sensor according to claim 2, characterized in that: The skylight background signal appears as a fan-shaped image on each sub-aperture, and the target signal is gathered at the vertex position of the fan-shaped image.

4. A target wavefront detection method using the pyramid wavefront sensor according to any one of claims 1 to 3, characterized in that: The steps include: S1. Calculate and remove the skylight value of each sub-aperture in each sub-pupil image formed by the detection camera using a skylight elimination algorithm to extract effective target signals; S2. Calculate the target's wavefront information according to the effective target signal.

5. The target wavefront detection method of the pyramid wavefront sensor according to claim 4, characterized in that: Step S1 includes the following sub-steps: S11, extracting all pixel points containing target signals and skylight background signals in the fan-shaped area of ​​each sub-aperture, and determining the coordinates of the pixel point with the maximum grayscale value among all the pixel points; S12, removing the pixel coordinates of the maximum gray value pixel and the pixels within a predetermined range around the pixel coordinates of the maximum gray value, leaving the remaining pixels; S13, calculate the average gray value of the remaining pixels With standard deviation σ i (x, y); where i represents the number of the sub-pupil image, and (x, y) represents the coordinates of the sub-aperture; S14, based on the average grayscale values ​​of the remaining pixels With standard deviation σ i (x, y), calculate the skylight value B for each sub-aperture i (x, y), the calculation formula is as follows: Where K represents the coefficient; S15. Subtract the corresponding skylight value B from each sub-aperture i (x, y), and extract the effective target signals I1, I2, I3, and I4 of each sub-pupil image; wherein I1, I2, I3, and I4 correspond to the upper left sub-pupil image, the upper right sub-pupil image, the lower right sub-pupil image, and the lower left sub-pupil image on the detection camera, respectively.

6. The target wavefront detection method of the pyramid wavefront sensor according to claim 5, characterized in that: In step S2, the target wavefront information S is calculated based on the effective target signals I1, I2, I3, and I4 of each sub-pupil image. x , and S y , the calculation formula is as follows:

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