MOSP: Monitor of Outer Scale profile

Ziad, Aziz; Maire, Jérôme; Borgnino, J.; Ali, Wassila Dali; Berdja, A.; Abdallah, Khaled Ben; Martin, F.; Sarazin, M.

doi:10.1051/ao4elt/201003008

Cited by 6 publications

(7 citation statements)

References 7 publications

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“…The profile in Fig. 14 has many characteristics common to other previously reported profiles obtained in independent campaigns (Dali et al 2010;Ziad et al 2013), where the maximum values of L 0 are obtained for altitudes between 1 and 2 km and the minimum values are located between 2 and 4 km.…”

Section: R E S U Lt S F O R L 0 ( H) From Gems T E L E M E T Rysupporting

confidence: 74%

“…This means that the use of a single L 0 is not adequate to describe the spatial coherence of the atmosphere, since the response function can be the result of combining slopes from more than one layer, each with different outer scale values, i.e. a profile or L 0 (h) (Coulman et al 1988;Lukin, Fortes & Nosov 1998;Dali et al 2010;Ziad et al 2013). …”

Section: Estimating the Integrated Lmentioning

confidence: 99%

“…The specific parameters (L 0 , h and ω) for each case are defined in Table 2; they have been arbitrarily chosen, similar to those reported in Ziad et al (2013) and Maire et al (2007). The table summarizes the results for the estimations of L 0 , h and ω, and case 1 (turbulence with four layers) is also plotted in Fig.…”

Section: Number Of Observable Layersmentioning

confidence: 99%

“…However, some studies have shown that it can vary significantly with altitude (Maire et al 2007;Dali et al 2010;Ziad et al 2013). This height-dependent outer scale, L 0 (h), has been introduced in the phase power spectrum of a von Kármán model by Borgnino, Martin & Ziad (1992):…”

Section: Introductionmentioning

confidence: 99%

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Online estimation of the wavefront outer scale profile from adaptive optics telemetry

Guesalaga

Neichel

Correia

et al. 2016

Mon. Not. R. Astron. Soc.

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Section: R E S U Lt S F O R L 0 ( H) From Gems T E L E M E T Rysupporting

confidence: 74%

Section: Estimating the Integrated Lmentioning

confidence: 99%

Section: Number Of Observable Layersmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Online estimation of the wavefront outer scale profile from adaptive optics telemetry

Guesalaga

Neichel

Correia

et al. 2016

Mon. Not. R. Astron. Soc.

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“…It is controlled by a dedicated software and has now attained a high level of automatisation. The present paper is an update of previous presentations [2,3,4]. It aims at giving the improvements and the present status of the instrument, and some statistics of turbulence above the Plateau de Calern.…”

Section: Introductionmentioning

confidence: 95%

Turbulence monitoring at the Plateau de Calern with the GDIMM instrument

Aristidi¹,

Yan²,

Chabé³

et al. 2018

Adaptive Optics Systems VI

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We present some statistics of turbulence monitoring at the Plateau de Calern (France), with the Generalised Differential Image Motion Monitor (GDIMM). This instrument allows to measure integrated parameters of the atmospheric turbulence, i.e. seeing, isoplanatic angle, coherence time and outer scale, with 2 minutes time resolution. It is running routinely since November 2015 and is now fully automatic. A large dataset has been collected, leading to the first statistics of turbulence above the Plateau de Calern.

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Real time characterization of atmospheric turbulence using speckle texture

Lochab,

Kumar,

Ghai

et al. 2023

J. Opt.

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A new method is proposed for the characterization of the atmospheric turbulence strength parameter ( C n 2 ) based on the principal component analysis (PCA) of the texture of the speckle intensity pattern obtained on long-range propagation of a focused charge +1 vortex beam. Employing the split-step propagation method, datasets containing instantaneous intensity images of the focused vortex beam are generated for three distinct C n 2 values, specifically 1 × 10 − 14 m − 2 / 3 , 5 × 10 − 14 m − 2 / 3 , and 1 × 10 − 13 m − 2 / 3 , representing medium to high turbulence levels for a 2 km propagation distance. The gray level co-occurrence matrix (GLCM) methodology is employed to extract key texture attributes, like contrast, correlation, homogeneity, and energy from the intensity images. These extracted texture parameters serve as inputs for training a PCA model, enabling the identification of associated C n 2 values. The PCA analysis exhibits distinct clustering of the first three principal components for each of the three C n 2 values, forming individual clusters on the PCA plot. Standard deviational ellipses are drawn to clearly demarcate these clusters on the PCA plot. The texture-based PCA classification of atmospheric turbulence was also performed for a focused Gaussian beam. The comparison of PCA plots between vortex and Gaussian beams showed that a pronounced clear separation of C n 2 values is obtained for the vortex beam. This indicates that the non-zero orbital angular momentum of the vortex beam also plays an important role in achieving the distinct separation of C n 2 values on the PCA plot. The proposed method can provide efficient real-time turbulence estimation solely on the basis of texture of the instantaneous intensity speckle with prior training and therefore may simplify the estimation of turbulence strength parameter.

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MOSP: Monitor of Outer Scale profile

Cited by 6 publications

References 7 publications

Online estimation of the wavefront outer scale profile from adaptive optics telemetry

Online estimation of the wavefront outer scale profile from adaptive optics telemetry

Turbulence monitoring at the Plateau de Calern with the GDIMM instrument

Real time characterization of atmospheric turbulence using speckle texture

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