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Performance of centroiding algorithms at low light level conditions in adaptive optics  [PDF]
Akondi Vyas,M. B. Roopashree,B. Raghavendra Prasad
Physics , 2010, DOI: 10.1109/ARTCom.2009.30
Abstract: The performance metrics of different centroiding algorithms at low light level conditions were optimized in the case of a Shack Hartmann Sensor (SHS) for efficient performance of the adaptive optics system. For short exposures and low photon flux, the Hartmann spot does not have a Gaussian shape due to the photon noise which follows Poissonian statistics. The centroiding estimation error was calculated at different photon levels in the case of changing spot size and shift in the spot using Monte Carlo simulations. This analysis also proves to be helpful in optimizing the SHS specifications at low light levels.
Error analysis of correlating Shack-Hartmann wave-front sensor for a point source

Chen Lin-Hui,Rao Chang-Hui,

物理学报 , 2011,
Abstract: In Shack-Hartmann wavefront sensor(SH-WFS) based adaptive optics system, the centroiding algorithm is usually used to estimate the centroid of a point source spot. But the detecting accuracy of the centroiding algorithm is affected by many factors such as threshold selection, so that the centroid position of the spot cannot be evaluated accurataly under the condition of low signal-to-noise ratio(SNR) . Comparatively the correlating algorithm for Shack-Hartmann wave front-sensing is more robust because it need not reduce the thresholding. In this paper, based on the the principle of the correlating SH-WFS, the measurement error of the correlating SH-WFS is derived by building up the noise model of the correlating SH-WFS. The influences of spot size, photon noise, read out noise and background light noise on the measurement of the correlating SH-WFS are analyzed systematically. The numerically simulation results and the experimental results are consistent well with the theoretical analyses.
Artificial neural networks for centroiding elongated spots in Shack-Hartmann wavefront sensors  [PDF]
A. T. Mello,A. Kanaan,D. Guzman,A. Guesalaga
Physics , 2014, DOI: 10.1093/mnras/stu427
Abstract: The use of Adaptive Optics in Extremely Large Telescopes brings new challenges, one of which is the treatment of Shack-Hartmann Wavefront sensors images. When using this type of sensors in conjunction with laser guide stars for sampling the pupil of telescopes with 30+ m in diameter, it is necessary to compute the centroid of elongated spots, whose elongation angle and aspect ratio are changing across the telescope pupil. Existing techniques such as Matched Filter have been considered as the best technique to compute the centroid of elongated spots, however they are not good at coping with the effect of a variation in the Sodium profile. In this work we propose a new technique using artificial neural networks, which take advantage of the neural network's ability to cope with changing conditions, outperforming existing techniques in this context. We have developed comprehensive simulations to explore this technique and compare it with existing algorithms.
Denoising Shack Hartmann Sensor spot pattern using Zernike Reconstructor  [PDF]
Akondi Vyas,M B Roopashree,B Raghavendra Prasad
Physics , 2009,
Abstract: Shack Hartmann Sensor (SHS) is inflicted with significant background noise that deteriorates the wave-front reconstruction accuracy. In this paper, a simple method to remove the back ground noise with the use of Zernike polynomials is suggested. The images corresponding to individual array points of the SHS at the detector, placed at the focal plane are independently reconstructed using Zernike polynomials by the calculation of Zernike moments. Appropriate thresholding is applied on the images. It is shown with computational experiments that using Zernike Reconstructor along with usual thresholding improves the centroiding accuracy when compared to direct thresholding. A study was performed at different Signal to Noise ratio by changing the number of Zernike orders used for reconstruction. The analysis helps us in setting upper and lower bounds in the application of this denoising procedure.
Laser Guide Stars for Extremely Large Telescopes: Efficient Shack-Hartmann Wavefront Sensor Design using Weighted center-of-gravity algorithm  [PDF]
L. Schreiber,I. Foppiani,C. Robert,E. Diolaiti,J. -M. Conan,M. Lombini
Physics , 2009, DOI: 10.1111/j.1365-2966.2009.14797.x
Abstract: Over the last few years increasing consideration has been given to the study of Laser Guide Stars (LGS) for the measurement of the disturbance introduced by the atmosphere in optical and near-infrared astronomical observations from the ground. A possible method for the generation of a LGS is the excitation of the Sodium layer in the upper atmosphere at approximately 90 km of altitude. Since the Sodium layer is approximately 10 km thick, the artificial reference source looks elongated, especially when observed from the edge of a large aperture. The spot elongation strongly limits the performance of the most common wavefront sensors. The centroiding accuracy in a Shack-Hartmann wavefront sensor, for instance, decreases proportionally to the elongation (in a photon noise dominated regime). To compensate for this effect a straightforward solution is to increase the laser power, i.e. to increase the number of detected photons per subaperture. The scope of the work presented in this paper is twofold: an analysis of the performance of the Weighted Center of Gravity algorithm for centroiding with elongated spots and the determination of the required number of photons to achieve a certain average wavefront error over the telescope aperture.
Evaluation of image-shift measurement algorithms for solar Shack-Hartmann wavefront sensors  [PDF]
Mats G. L?fdahl
Physics , 2010, DOI: 10.1051/0004-6361/201015331
Abstract: Context. Solar Shack-Hartmann wavefront sensors measure differential wavefront tilts as the relative shift between images from different subapertures. There are several methods in use for measuring these shifts. Aims. We evaluate the inherent accuracy of the methods and the effects of various sources of error, such as noise, bias mismatch, and blurring. We investigate whether Z-tilts or G-tilts are measured. Methods. We test the algorithms on two kinds of artificial data sets, one corresponding to images with known shifts and one corresponding to seeing with different r_0. Results. Our results show that the best methods for shift measurements are based on the square difference function and the absolute difference function squared, with subpixel accuracy accomplished by use of two-dimensional quadratic interpolation. These methods measure Z-tilts rather than G-tilts.
Shack-Hartmann sensor improvement using optical binning  [PDF]
Alastair Basden,Deli Geng,Dani Guzman,Tim Morris,Richard Myers,Chris Saunter
Physics , 2007, DOI: 10.1364/AO.46.006136
Abstract: We present a design improvement for a recently proposed type of Shack-Hartmann wavefront sensor that uses a cylindrical (lenticular) lenslet array. The improved sensor design uses optical binning and requires significantly fewer detector pixels than the corresponding conventional or cylindrical Shack-Hartmann sensor, and so detector readout noise causes less signal degradation. Additionally, detector readout time is significantly reduced, which reduces the latency for closed loop systems, and data processing requirements. We provide simple analytical noise considerations and Monte-Carlo simulations, and show that the optically binned Shack-Hartmann sensor can offer better performance than the conventional counterpart in most practical situations, and our design is particularly suited for use with astronomical adaptive optics systems.
A Self-reference Method for Measuring Hartmann-Shack Wavefront Sensor Parameter

LIANG Chun,SHENG Jian-xin,TONG Gui,LI Bang-ming,

光子学报 , 2009,
Abstract: A new method is proposed to measure the parameter of Hartmann-Shack wavefront sensor.It was based on the Zernike polynomial modal reconstruction algorithm,and can be used to obtain the distance between micro-lens array and the CCD accurately.It obviously reduces the error caused by the slope calculation using micro-lens focus instead of actual parameter.Through this way,the requirement of sensor assembly-precision is reduced,and the detection accuracy of Hartmann-Shack sensor is also improved in the meanwhi...
Detection of phase singularities with a Shack-Hartmann wavefront sensor  [PDF]
Mingzhou Chen,Filippus S. Roux,Jan C. Olivier
Physics , 2006, DOI: 10.1364/JOSAA.24.001994
Abstract: While adaptive optical systems are able to remove moderate wavefront distortions in scintillated optical beams, phase singularities that appear in strongly scintillated beams can severely degrade the performance of such an adaptive optical system. Therefore, the detection of these phase singularities is an important aspect of strong scintillation adaptive optics. We investigate the detection of phase singularities with the aid of a Shack-Hartmann wavefront sensor and show that, in spite of some systematical deficiencies inherent to the Shack-Hartmann wavefront sensor, it can be used for the reliable detection of phase singularities, irrespective of their morphologies. We provide full analytical results, together with numerical simulations of the detection process.
Error propagation: a comparison of Shack-Hartmann and curvature sensors  [PDF]
A. N. Kellerer,A. M. Kellerer
Physics , 2011, DOI: 10.1364/JOSAA.28.000801
Abstract: Phase estimates in adaptive-optics systems are computed by use of wavefront sensors such as Shack-Hartmann or curvature sensors. In either case the standard error of the phase estimates is proportional to the standard error of the measurements; but the error-propagation factors are different. We calculate the ratio of these factors for curvature and Shack-Hartmann sensors in dependence on the number of sensors, n, on a circular aperture. If the sensor spacing is kept constant and the pupil is enlarged, the ratio increases as n^0.4. When more sensing elements are accommodated on the same aperture, it increases even faster, viz. proportional to n^0.8. With large numbers of sensing elements this increase can limit the applicability of curvature sensors.
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