Measurement and Data Processing Approach for Detecting Anisotropic Spatial Statistics of the Turbulence-Induced Index of Refraction Fluctuations in the Upper Atmosphere
Applied Optics, Vol. 41, Issue 15, pp. 2800-2808 (2002)
http://dx.doi.org/10.1364/AO.41.002800
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Abstract
We discuss a method of data reduction and analysis that has been developed for a novel experiment to detect anisotropic turbulence in the tropopause and to measure the spatial statistics of these flows. The experimental concept is to make measurements of temperature at 15 points on a hexagonal grid for altitudes from 12,000 to 18,000 m while suspended from a balloon performing a controlled descent. From the temperature data, we estimate the index of refraction and study the spatial statistics of the turbulence-induced index of refraction fluctuations. We present and evaluate the performance of a processing approach to estimate the parameters of an anisotropic model for the spatial power spectrum of the turbulence-induced index of refraction fluctuations. A Gaussian correlation model and a least-squares optimization routine are used to estimate the parameters of the model from the measurements. In addition, we implemented a quick-look algorithm to have a computationally nonintensive way of viewing the autocorrelation function of the index fluctuations. The autocorrelation of the index of refraction fluctuations is binned and interpolated onto a uniform grid from the sparse points that exist in our experiment. This allows the autocorrelation to be viewed with a three-dimensional plot to determine whether anisotropy exists in a specific data slab. Simulation results presented here show that, in the presence of the anticipated levels of measurement noise, the least-squares estimation technique allows turbulence parameters to be estimated with low rms error.
© 2002 Optical Society of America
OCIS Codes
(010.7060) Atmospheric and oceanic optics : Turbulence
Citation
Timothy C. Havens, Michael C. Roggemann, Timothy J. Schulz, Wade W. Brown, Jeff T. Beyer, and L. John Otten, "Measurement and Data Processing Approach for Detecting Anisotropic Spatial Statistics of the Turbulence-Induced Index of Refraction Fluctuations in the Upper Atmosphere," Appl. Opt. 41, 2800-2808 (2002)
http://www.opticsinfobase.org/ao/abstract.cfm?URI=ao-41-15-2800
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References
- M. C. Roggemann and B. M. Welsh, Imaging Through Turbulence (CRC Press, Boca Raton, Fla., 1996).
- J. W. Goodman, Statistical Optics (Wiley, New York, 1985).
- A. N. Kolmogorov, “The local structure of turbulence in incompressible viscous fluids for very large Reynolds’ numbers,” in Turbulence, Classic Papers on Statistical Theory, S. K. Friedlander and L. Topper, eds. (Wiley-Interscience, New York, 1961), pp. 151–155.
- V. I. Tatarskii, Wave Propagation in a Turbulent Medium (Dover, New York, 1967).
- D. L. Fried, “Optical resolution through a randomly inhomogeneous medium for very long and very short exposures,” J. Opt. Soc. Am. 56, 1372–1379 (1966).
- D. L. Fried, “Anisoplanatism in adaptive optics,” J. Opt. Soc. Am. 72, 52–61 (1982).
- R. R. Beland, “Propagation through atmospheric optical turbulence,” in The Infrared and Electro-Optical Systems Handbook, Vol. PM 10 of the SPIE Press Monographs, J. S. Accetla and D. L. Shumaker, eds. (SPIE, Bellingham, Wash., 1993), Vol. 1, Chap. 2.
- P. J. Gardner, M. C. Roggeman, B. M. Welsh, R. D. Bowersox, and T. E. Luke, “Statistical anisotropy in free turbulence for mixing layers at high Reynolds numbers,” Appl. Opt. 35, 4879–4889 (1996).
- P. J. Gardner, M. C. Roggeman, B. M. Welsh, R. D. Bowersox, and T. E. Luke, “Comparison of measured and computed Strchl ratios for light propagated through a channel flow of a He/N_{2} mixing layer at high Reynolds numbers,” Appl. Opt. 36, 2559–2576 (1997).
- L. V. Antoshkin, N. N. Botygina, O. N. Emaleev, L. N. Lavrinova, V. P. Lukin, A. P. Rostov, B. V. Fortes, and A. P. Yankov, “Investigation of turbulence spectrum anisotropy in the ground atmospheric layer: preliminary results,” Atmos. Oceanic Opt. 8, 993–996 (1995).
- F. Dalaudier, C. Sidi, M. Crochet, and J. Vernin, “Direct evidence of sheets in the atmospheric temperature field,” J. Atmos. Sci. 51, 237–248 (1994).
- L. J. Otten, D. T. Kyrazis, D. W. Tyler, and N. Miller, “Implications of atmospheric models on adaptive optics designs,” in Symposium on Astronomical Telescopes and Instrumentation for the 21st Century, M. A. Ealey and F. Merkle, eds. (SPIE, Bellingham, Wash, 1994), Vol. 2201, pp. 201–211.
- A. Mahalov, B. Nicolaenko, and Y. Zhou, “Energy spectra of strongly stratified and rotating turbulence,” Phys. Rev. E 57, 6187–6190 (1998).
- W. W. Brown, M. C. Roggemann, T. J. Schulz, T. C. Havens, J. T. Beyer, and L. J. Otten, “Measurement and data processing approach for estimating the spatial statistics of turbulence-induced index of refraction fluctuations in the upper atmosphere,” Appl. Opt. 40, 1863–1871 (2001).
- R. Barakat and J. W. Beletic, “Influence of atmospherically induced random wave fronts on diffraction imagery: a computer simulation model for testing image reconstruction algorithms,” J. Opt. Soc. Am. A 7, 653–671 (1990).
- J. A. Melsa and D. L. Cohn, Decision and Estimation Theory (McGraw-Hill, New York, 1978).
- M. A. Branch and A. Grace, MATLAB Optimization Toolbox (The Math Works, Natick, Mass., 1996).
- MATLAB Reference Guide (The Math Works, Natick, Mass., 1996).
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