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Jean-Pierre Véran AO4ELT3, 27-31 May 2013

Improved Tilt Sensing in an LGS-based Tomographic AO System Based on Instantaneous PSF Estimation. Jean-Pierre Véran AO4ELT3, 27-31 May 2013. AO fields (NFIRAOS). 17”x17” science field. 70” diameter LGS asterism. 120” diameter “technical” field To pick-off NGS sources

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Jean-Pierre Véran AO4ELT3, 27-31 May 2013

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  1. Improved Tilt Sensing in an LGS-basedTomographicAO System Based on Instantaneous PSF Estimation Jean-Pierre Véran AO4ELT3, 27-31 May 2013

  2. AO fields (NFIRAOS) • 17”x17” science field • 70” diameter LGS asterism • 120” diameter “technical” field • To pick-off NGS sources • Used to sense tip, tilt and tilt anisoplanatism (NGS modes) • All LGS-based MCAO, LTAO MOAO systems have a similar arrangement

  3. NGS modes in a tomographic LGS system • NGS modes = tip, tilt and tilt anisoplanatism • How well we can correct the NGS modes sets the sky coverage • For NFIRAOS, 3 NGSs (2 T/T and 1 2x2 Shack-Hartmann) • Problem: NGSs are usually far away from the science field and are therefore poorly corrected (even if MCAO is implemented) • Spot centroiding error • Decreases with sharper core • Decreases with higher number of photons in the core • Spot centroiding error propagates to reduce NGS mode correction

  4. Mitigation #1Improved control • A more sophisticated control strategy allows increasing the exposure time (so more photons in the core) without being severely penalized by the increase in servo-lag error • Increased sky coverage with optimal correction of tilt and tilt-anisoplanatism modes in laser-guide-star multiconjugate adaptive optics, Correia, Carlos; Véran, Jean-Pierre; Herriot, Glen; Ellerbroek, Brent; Wang, Lianqi; Gilles, Luc, JOSA A, vol. 30, issue 4, p. 604, 2013 • Uses LQG control of all the NGS modes • Improves the sky coverage by ~20% on NFIRAOS, compared to simple type-I control

  5. Mitigation #2Image sharpening • Use a DM in each of the NGS WFS paths to sharpen the NGS spots • The DM is driven based on a wave-front estimate in the direction of the NGS, derived from the current 3D estimate of the turbulence obtained from the LGSs • Pros: • Potential for spectacular improvements in sky coverage • Cons: • DM is driven in open-loop • Significant increase in cost and in complexity (opto-mechanics + software)

  6. NGS sharpening on NFIRAOS Lianqi Wang, TMT

  7. Spot centroiding using long exposure reference • NFIRAOS baseline: unconstrained matched filters, based on Gaussian fit to long exposure spot image. • Example: H-band, WFE=600nm RMS (SR=0.4%), PDE=600, rn=3e-, TT=0mas RMS, 100 uncorrelated spot images, 8x8 pixels, 5.5mas/pixel (Nyquist) Examples of instantaneous spot images Gaussian fit Average spot image Corresponding instantaneous PSFs X-filter Y-filter

  8. Spot centroiding using short exposure reference • Short exposure spot image (instantaneous PSF) can be estimated from the tomographic estimate of the turbulence volume obtained from the LGSs. • Similar process to estimating the DM drive commands for image sharpening • The estimate of the instantaneous PSF can be used for better centroiding • Matched filter are no longer attractive because no analytical model for instantaneous PSF. However, other centroiding techniques can be used such as: • Correlation • PSF fitting

  9. Inspiration • Deconvolution from wave-front sensing (DWFS) • Deconvolution from wave-front sensing: a new technique for compensating turbulence-degraded images, J. Primot, G. Rousset, and J. C. Fontanella, JOSA A, Vol. 7, Issue 9, pp. 1598-1608 (1990) • Use WFS measurements to aid speckle imaging • Improves performance of traditional speckle imaging techniques • Early days of AO

  10. PSF fitting • Find (a,b,c) that minimize: Where: I(x,y) is the recorded spot image, PSF(x,y) is the estimated instantaneous PSF, and σx,y is the noise at each pixel. • Carry out the minimization in the Fourier domain, using the Levenberg-Marquardt algorithm for quick convergence • Trivial case of finding the photometry and astrometry of a stellar field image knowing the PSF (only one star here!)

  11. SimulationStep 1: Creation • Create 100 random phase screens with spatial frequency distribution f^[-2,-3] • For each screen • Remove P/T/T and renormalize to RMS=[100,300,600] • Create instantaneous PSF • Scale total to [100,200,300,400,500,600] PDE (store S1) • Apply tilt=N(0,[0,0.1,0.2,0.3,0.4,0.5])pix • Apply [8x8,4x4] window (store S2) • Apply photon + readout noise (3e-) (store S3) • Compute: • Long exposure PSF (from S3) • Unconstrained matched filters (from LEPSF + 3e- noise)

  12. SimulationStep 2: Processing • For each image: • Apply matched filter • Correlate with long exposure PSF and find maximum of correlation function • Correlate with instantaneous PSF and find maximum of correlation function • Apply PSF fitting using long exposure PSF • Apply PSF fitting using instantaneous PSF

  13. Preliminary results NFIRAOS pure tilt residual ~ 1mas RMS or 0.2pix RMS

  14. Conclusion • Improved centroiding using an estimate of the instantaneous PSF might be an interesting alternative to image sharpening • Implementation only requires a bit of additional software • Work in progress • Preliminary results are encouraging • PSF fitting could probably be improved by not trying to estimate the amplitude of the PSF from each image • Use amplitude of long exposure PSF instead • Errors in estimating the instantaneous PSF needs to be addressed

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