基于EEMD的光学湍流廓线确定项与随机项分析

为了可靠地评估大气的光束传播效应, 必须确定大气光学湍流的路径分布。采用高分辨率无线电探空仪探测光学湍流强度的垂直分布,利用集合经验模态分解将其分解为不同尺度的本征模态分量, 并分析了不同分量变化的周期性及对整体变化的贡献。结果表明,部分本征模态函数分量具有周期性, 并通过了周期显著性检验; 方差贡献率表明整体趋势变化和随机强噪声是大气光学湍流廓线随高度变化的主要原因。利用基于连续均方误差准则的滤波方法实现了大气光学湍流确定项和随机项的分离,相关分析得到背景水平和统计平均值相关系数大于0.99。并分析随机项得出光学湍流随机项是非平稳序列且具有多重分形结构。

Abstract

Knowledge of distribution of atmospheric optical turbulence in propagation path is indispensable to evaluate the optical propagation effects accurately. Vertical profiles of optical turbulence strength are obtained from balloon flights. The data are decomposed into intrinsic mode functions on different scales by ensemble empirical mode decomposition. The quasi-cyclical variations on different components as well as their contribution to entire profile are analyzed. The results show that the cyclical scale within some intrinsic mode components is confirmed passing the statistical significance. Variance contribution rates show that the overall trend and stochastic intense noise are the main cause for the optical turbulence variation. A signal-filtering method based on consecutive mean square error is used to separate the profile into background and stochastic term. Correlation analysis of background and statistical mean show that the correlation coefficient is larger than 0.99. Analysis of stochastic term indicates that the optical turbulence profile is nonstationary series with multifractal structure.

参考文献

[1] Andrews L C, Phillips R L. Laser beam propagation through random media［M］. Bellingham: SPIE Optical Engineering Press, 2005: 57-82.

[2] 饶瑞中. 现代大气光学［M］. 北京: 科学出版社, 2012: 68-218.

Rao Ruizhong. Modern atmospheric optics［M］. Beijing: Science Press, 2012: 68-218.

[3] Beland R R. Propagation through atmospheric optical turbulence［M］. Bellingham: SPIE Optical Engineering Press, 1993: 159-223.

[4] Coulman C E, Vernin J, Fuchs A. Optical seeing-mechanism of formation of thin turbulent laminae in the atmosphere［J］. Applied Optics, 34(24): 5461-5474.

[5] Racine R, Ellerbroek B L. Profiles of nighttime turbulence above Mauna Kea and isoplanatism extension in adaptive optics［C］. SPIE, 1995: 248-257.

[6] Azouit M, Vernin J. Optical turbulence profiling with balloons relevant to astronomy and atmospheric physics［J］. Publications of the Astronomical Society of the Pacific, 2005, 117(831): 536-543.

[7] 翁宁泉, 肖黎明, 龚知本. 折射率结构常数廓线模式讨论［J］. 大气与环境光学学报, 2007, 2(1): 16-22.

Weng Ningquan, Xiao Liming, Gong Zhiben. Refractive index structure constant profile and the average model［J］. Journal of Atmospheric and Environmental Optics, 2007, 2(1): 16-22.

[8] Stull R B. An introduction to boundary layer meteorology［M］. Dordrecht: KluwerAcademic Publishers, 1988: 29-74.

[9] Huang N E, Shen Z, Long S R, et al. The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis［C］. Proceedings of the Royal Society of London A: Mathematical, Physical and Engineering Sciences, 1998, 454(1971): 903-995.

[10] Wu Z H, Huang N E. Ensemble empirical mode decomposition: A noise assisted data analysis method［J］. Advances in Adaptive Data Analysis, 2009, 1(1): 1-41.

[11] Wu Z H, Huang N E. A study of the characteristics of white noise using the empirical mode decomposition using the empirical mode decomposition method［C］. Proceedings of the Royal Society of London A: Mathematical, Physical and Engineering Sciences, 2004, 460(2046): 1597-1611.

[12] Flandrin P, Rilling G, Goncalves P. Empirical mode decomposition as a filter bank［J］. IEEE Signal Processing Letters, 2004, 11(2): 112-114.

[13] Huang N E, Wu M L C, Long S R, et al. A confidence limit for the empirical mode decomposition and Hilbert spectral analysis［C］. Proceedings of the Royal Society of London A: Mathematical, Physical and Engineering Sciences, 2003, 459(2037): 2317-2345.

[14] Huang N E, Wu Z. A review on Hilbert-Huang transform: Method and its applications to geophysical studies［J］. Reviews of Geophysics, 2008, 46(2): RG2006.

[15] 蒋立辉, 盖井艳, 王维波, 等. 基于总体平均经验模态分解的光纤周界预警系统模式识别方法［J］. 光学学报, 2015, 35(10): 1006002.

Jiang Lihui, Gai Jingyan, Wang Weibo, et al. Ensemble empirical mode decomposition based event classification method for the fiber-Optic intrusion monitoring system［J］. Acta Optica Sinica, 2015, 35(10): 1006002.

[16] Lagubeau G, Cobelli P, Bobinski T, et al. Empirical mode decomposition profilometry: small-scale capabilities and comparison to Fourier transform profilometry［J］. Applied Optics, 2015, 54(32): 9409-9414.

[17] Breaker L C, Ruzmaikin A. The 154-year record of sea level at San Francisco: extracting the long-term trend, recent changes, and other tidbits［J］. Climate Dynamics, 2011, 36(3): 545-559.

[18] Coulman C E, Vernin J, Fuchs A. Optical seeing-mechanism of formation of thin turbulent laminae in the atmosphere［J］. Applied Optics, 1995, 34(24): 5461-5474.

[19] Bufton J L. Comparison of vertical profile turbulence structure with stellar observations［J］. Applied Optics, 1973, 12(8): 1785-1793.

[20] Bufton J L. Correlation of microthermal turbulence data with meteorological soundings in the troposphere［J］. Journal of Atmospheric Sciences, 1972, 30(1): 83-87.

[21] Huang N E, Shen S S P. Hilbert-Huang transform and its applications［M］. Singapore: World Scientific, 2014: 1-222.

[22] Torrence C, Compo G P. A practical guide to wavelet analysis［J］. Bulletin of American Meteorological Society, 1998, 79(1): 61-78.

[23] Kantelhardt J W, Zschiegner S A, Koscielny-Bunde E, et al. Multifractal detrended fluctuation analysis of nonstationary time series［J］. Physica A Statistical Mechanics & Its Applications, 2002, 316(1): 87-114.

[24] Telesca L, Colangelo G, Lapenna V, et al. Fluctuation dynamics in geoelectrical data: An investigation by using multifractal detrended fluctuation analysis［J］. Physics Letters A, 2004, 332(5): 398-404.

[25] Barille R, Lapenna P. Multifractality of laser beam spatial intensity in a turbulent medium［J］. Applied Optics, 2006, 45(14): 3331-3339.

[26] Lopez J L, Contreras J G. Performance of multifractal detrended fluctuation analysis on short time series［J］. Physical Review E, 2013, 87(2): 022918.

[27] Thompson J R, Wilson J R, Beauwens R. Multifractal detrended fluctuation analysis: Practical applications to financial time series［J］. Mathematics & Computers in Simulation, 2016, 126: 63-88.

[28] Mali P. Multifractal characterization of global temperature anomalies［J］. Theoretical and Applied Climatology, 2015, 121(3-4): 641-648.

陈小威, 李学彬, 孙刚, 刘庆, 朱文越, 翁宁泉. 基于EEMD的光学湍流廓线确定项与随机项分析[J]. 光学学报, 2017, 37(1): 0101001. Chen Xiaowei, Li Xuebin1, Sun Gang, Liu Qing, Zhu Wenyue, Weng Ningquan. Background and Stochastic Terms of Optical Turbulence Profile Based on Ensemble Empirical Mode Decomposition[J]. Acta Optica Sinica, 2017, 37(1): 0101001.

基于EEMD的光学湍流廓线确定项与随机项分析

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