Literature DB >> 11583270

Optimal wave-front reconstruction strategies for multiconjugate adaptive optics.

T Fusco1, J M Conan, G Rousset, L M Mugnier, V Michau.   

Abstract

We propose an optimal approach for the phase reconstruction in a large field of view (FOV) for multiconjugate adaptive optics. This optimal approach is based on a minimum-mean-square-error estimator that minimizes the mean residual phase variance in the FOV of interest. It accounts for the C2n profile in order to optimally estimate the correction wave front to be applied to each deformable mirror (DM). This optimal approach also accounts for the fact that the number of DMs will always be smaller than the number of turbulent layers, since the C2n profile is a continuous function of the altitude h. Links between this optimal approach and a tomographic reconstruction of the turbulence volume are established. In particular, it is shown that the optimal approach consists of a full tomographic reconstruction of the turbulence volume followed by a projection onto the DMs accounting for the considered FOV of interest. The case where the turbulent layers are assumed to match the mirror positions [model-approximation (MA) approach], which might be a crude approximation, is also considered for comparison. This MA approach will rely on the notion of equivalent turbulent layers. A comparison between the optimal and MA approaches is proposed. It is shown that the optimal approach provides very good performance even with a small number of DMs (typically, one or two). For instance, good Strehl ratios (greater than 20%) are obtained for a 4-m telescope on a 150-arc sec x 150-arc sec FOV by using only three guide stars and two DMs.

Entities:  

Year:  2001        PMID: 11583270     DOI: 10.1364/josaa.18.002527

Source DB:  PubMed          Journal:  J Opt Soc Am A Opt Image Sci Vis        ISSN: 1084-7529            Impact factor:   2.129


  3 in total

1.  Increasing the field of view of adaptive optics scanning laser ophthalmoscopy.

Authors:  Marie Laslandes; Matthias Salas; Christoph K Hitzenberger; Michael Pircher
Journal:  Biomed Opt Express       Date:  2017-10-03       Impact factor: 3.732

2.  An ANN-based smart tomographic reconstructor in a dynamic environment.

Authors:  Francisco J de Cos Juez; Fernando Sánchez Lasheras; Nieves Roqueñí; James Osborn
Journal:  Sensors (Basel)       Date:  2012-06-27       Impact factor: 3.576

3.  Comparative Study of Neural Network Frameworks for the Next Generation of Adaptive Optics Systems.

Authors:  Carlos González-Gutiérrez; Jesús Daniel Santos; Mario Martínez-Zarzuela; Alistair G Basden; James Osborn; Francisco Javier Díaz-Pernas; Francisco Javier De Cos Juez
Journal:  Sensors (Basel)       Date:  2017-06-02       Impact factor: 3.576

  3 in total

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