Citation: |
|
[1] | Jiang W H, Li M Q, Tang G M, et al. Adaptive optical image compensation experiments on stellar objects[J]. Opt Eng, 1995, 34(1): 15-20. doi: 10.1117/12.184078 |
[2] | Zhang R J, Li H G. Hartmann-Shack wavefront sensing and wavefront control algorithm[J]. Proc SPIE, 1990, 1271: 82-93. doi: 10.1117/12.20396 |
[3] | 姜文汉, 鲜浩, 杨泽平, 等. 哈特曼波前传感器的应用[J]. 量子电子学报, 1995, 15(2): 228-235. Jiang W H, Xian H, Yang Z P, et al. Applications of Shack-Hartmann wavefront sensor[J]. J Quantum Electron, 1995, 15(2): 228-235. |
[4] | Li H G, Jiang W H. Application of H-S wavefront sensor for quality diagnosis of optical system and light beam[C]//ICO-16 Satellite Conference on Active and Adaptive Optics, 1993: 369-376. |
[5] | 陈浩, 魏凌, 李恩德, 等. 基于B样条函数的快速波前复原[J]. 光电工程, 2021, 48(2): 60-69. doi: 10.12086/oee.2021.200160 Chen H, Wei L, Li E D, et al. A B-spline based fast wavefront reconstruction algorithm[J]. Opto-Electron Eng, 2021, 48(2): 60-69. doi: 10.12086/oee.2021.200160 |
[6] | Li C H, Xian H, Rao C H, et al. Field-of-view shifted Shack-Hartmann wavefront sensor for daytime adaptive optics system[J]. Opt Lett, 2006, 31(19): 2821-2823. doi: 10.1364/OL.31.002821 |
[7] | 姜文汉, 鲜浩, 沈锋. 夏克-哈特曼波前传感器的探测误差[J]. 量子电子学报, 1998, 15(2): 218-227. Jiang W H, Xian H, Shen F. Detection error of Shack-Hartmann wavefront sensor[J]. J Quantum Electron, 1998, 15(2): 218-227. |
[8] | Beckers J M, Cacciani A. Using laser beacons for daytime adaptive optics[J]. Experimental Astronomy, 2001, 11(2): 133-143. doi: 10.1023/A:1011140920850 |
[9] | Gonglewski J D, Highland R G, Dayton D C, et al. ADONIS: Daylight imaging through atmospheric turbulence[J]. Proc SPIE, 1996, 2827: 152-161. doi: 10.1117/12.255078 |
[10] | 徐维安. 光谱滤波装置在白天测星中的应用[J]. 光学精密工程, 1996, 4(4): 84-88. doi: 10.3321/j.issn:1004-924X.1996.04.016 Xu W A. Application of spectral filter device in measuring stellar daytime[J]. Opt Precis Eng, 1996, 4(4): 84-88. doi: 10.3321/j.issn:1004-924X.1996.04.016 |
[11] | 李旭旭, 李新阳, 王彩霞. 哈特曼传感器子孔径光斑的局部自适应阈值分割方法[J]. 光电工程, 2018, 45(10): 170699. doi: 10.12086/oee.2018.170699 Li X X, Li X Y, Wang C X. Local adaptive threshold segmentation method for subaperture spot of Shack-Hartmann sensor[J]. Opto-Electron Eng, 2018, 45(10): 170699. doi: 10.12086/oee.2018.170699 |
[12] | 张锐进, 鲜浩, 饶长辉, 等. 偏振滤波白天抑制天光背景作用分析[J]. 光学学报, 2012, 32(5): 0501003. doi: 10.3788/AOS201232.0501003 Zhang R J, Xian H, Rao C H, et al. study on effect of polarization filter for suppressing sky background light in daytime[J]. Acta Opt Sin, 2012, 32(5): 0501003. doi: 10.3788/AOS201232.0501003 |
[13] | 范真涛, 汤媛媛, 魏凯, 等. 光谱椭偏系统光源和光谱仪偏振相关系数测量[J]. 光电工程, 2019, 46(12): 180507. doi: 10.12086/oee.2019.180507 Fan Z T, Tang Y Y, Wei K, et al. Measurement of polarization correlation coefficients of light source and spectrometer in spectroscopic ellipsometry[J]. Opto-Electron Eng, 2019, 46(12): 180507. doi: 10.12086/oee.2019.180507 |
Overview: After more than 40 years of continuous development, adaptive optics has gradually matured in theoretical exploration and engineering applications, and has been widely used in various fields. The Hartmann wavefront sensor is an important part of the adaptive optics system and is currently the most widely used wavefront detector in the adaptive optics system. When the Hartmann wavefront sensor performs wavefront detection in strong background occasions like daytime, the interference of the strong background will increase the centroid calculation error in the wavefront calculation and significantly reduce the wavefront detection accuracy, which severely limits working hours of the adaptive optics system.
Aiming at the application scenario of a large back-to-signal ratio, a new polarized Hartmann wavefront detection technology is proposed. The polarized Hartmann wavefront detector adds a polarization modulator in front of the microlens array to obtain intensity detection images under different polarization modulation states. The polarized difference principle is used to convert the directly detected intensity signal into a polarization signal, and finally, the Hartmann wavefront detection result is transformed from the intensity dimension to the polarization dimension by using the difference between the polarization characteristics of the detection target and the background light. This article describes the basic methods and principles of polarized Hartmann wavefront detection technology, and then conducts numerical simulations for linear polarization signal wavefront detection in natural light scenes, which are as follows. First, the wavefront restoration results before and after adding the strong background are compared to clarify the influence of the strong background on the Hartmann wavefront restoration results. Then, the strong background processing and wavefront restoration calculation under different back signal ratios are launched. Finally, the removal effect of the strong background and the wavefront restoration error of the subtracted global threshold method, subtracted local adaptive threshold method, and polarization difference method is compared.
Theoretical and simulation results show that the polarized Hartmann wavefront detection technology has a good removal effect on strong background, and has high wavefront restoration accuracy. This improves the signal-to-background ratio of Hartmann wavefront detection to a certain extent, and improves the accuracy of wavefront detection under strong background conditions. Therefore, the polarization Hartmann wavefront detection technology has high feasibility for wavefront detection in strong background scenes, and has a great effect on the application expansion of adaptive optics in daytime scenes.
Schematic map of the Hartmann sensor under the strong background scene
Spot array of the Hartmann-Shack wavefront sensor.
Basic principle of the proposed polarization Hartmann wavefront sensor
Schematic map of the polarization state of mixed light.
Schematic map of polarization modulation of the polarization Hartmann sensor
Reference signal sub-aperture spot image and its restored wavefront and Zernike coefficient.
Mixed signal sub-aperture spot image and its wavefront restoration image and wavefront Zernike coefficients.
Sub-aperture spot image processed by various methods for strong background.
The restored wavefront image and its Zernike coefficient expression after three processing methods.
Wavefront restoration error using different methods.
RMS value curve of wavefront restoration error for different RBS.