Literature DB >> 18264477

Evaluation of least-squares phase-diversity technique for space telescope wave-front sensing.

D J Lee, M C Roggemann, B M Welsh, E R Crosby.   

Abstract

Because of mechanical aspects of fabrication, launch, and operational environment, space telescope optics can suffer from unforeseen aberrations, detracting from their intended diffraction-limited performance goals. We give the results of simulation studies designed to explore how wave-front aberration information for such near-diffraction-limited telescopes can be estimated through a regularized, low-pass filtered version of the Gonsalves (least-squares) phase-diversity technique. We numerically simulate models of both monolithic and segmented space telescope mirrors; the segmented case is a simplified model of the proposed next generation space telescope. The simulation results quantify the accuracy of phase diversity as a wave-front sensing (WFS) technique in estimating the pupil phase map. The pupil phase is estimated from pairs of conventional and out-of-focus photon-limited point-source images. Image photon statistics are simulated for three different average light levels. Simulation results give an indication of the minimum light level required for reliable estimation of a large number of aberration parameters under the least-squares paradigm. For weak aberrations that average a 0.10lambda pupil rms, the average WFS estimation errors obtained here range from a worst case of 0.057lambda pupil rms to a best case of only 0.002lambda pupil rms, depending on the light level as well as on the types and degrees of freedom of the aberrations present.

Year:  1997        PMID: 18264477     DOI: 10.1364/ao.36.009186

Source DB:  PubMed          Journal:  Appl Opt        ISSN: 1559-128X            Impact factor:   1.980


  1 in total

1.  High-accuracy wavefront sensing by phase diversity technique with bisymmetric defocuses diversity phase.

Authors:  Peiguang Zhang; Chengliang Yang; Zihao Xu; Zhaoliang Cao; Quanquan Mu; Li Xuan
Journal:  Sci Rep       Date:  2017-11-10       Impact factor: 4.379

  1 in total

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