Imaging Components, Systems, and Processing

Zonal representation–based residual-wavefront reconstruction using multiframe Shack-Hartmann measurements

[+] Author Affiliations
Shiping Guo, Jisheng Li, Jianhua Zou

Xi’an Jiaotong University, Systems Engineering Institute, Jiaoda Cooperation Department of ADL, No. 28, Xianning West Road, Xi’an 710049, China

Rongzhi Zhang, Rong Xu, Changhai Liu

Xi’an Satellite Control Center, State Key Laboratory of Astronautic Dynamics, No. 426, Xianning East Road, Xi’an 710043, China

Opt. Eng. 54(11), 113105 (Nov 12, 2015). doi:10.1117/1.OE.54.11.113105
History: Received March 25, 2015; Accepted October 9, 2015
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Abstract.  Atmospheric turbulence-induced wavefront deformation can be only partially corrected by adaptive optics (AO) techniques in astronomical or artificial space object imaging; an accurate estimation of the residual-wavefront phase is still needed to approach the diffraction-limited resolution. The discrete phase gradients measured by Shack-Hartmann wavefront sensors (SHWFS) can help with the estimation. In this study, we build a dynamic average slopes measurement model for SHWFS in short-exposure AO images postprocessing; the proposed model is based on a zonal representation of the wavefront phase using Bernstein basis polynomials instead of the traditional Zernike modal expansion. Further, the turbulence’s frozen flow hypothesis is adopted to update the initial model using multiframe SHWFS measurement data to achieve a more accurate reconstruction. Numerical experiments show the reconstruction errors significantly decrease even in poor seeing conditions, and show that our method is less sensitive to different SHWFS measurement noise levels.

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© 2015 Society of Photo-Optical Instrumentation Engineers

Citation

Shiping Guo ; Rongzhi Zhang ; Jisheng Li ; Jianhua Zou ; Rong Xu, et al.
"Zonal representation–based residual-wavefront reconstruction using multiframe Shack-Hartmann measurements", Opt. Eng. 54(11), 113105 (Nov 12, 2015). ; http://dx.doi.org/10.1117/1.OE.54.11.113105


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