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Generalized modified atmospheric spectral model for optical wave propagating through non-Kolmogorov turbulence

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A new generalized modified atmospheric spectral model is derived theoretically for wave propagating through non-Kolmogorov turbulence, which has been reported recently by increasing experimental evidence and theoretical investigation. The generalized, modified atmospheric spectrum considers finite turbulence inner and outer scales and has a spectral power law value in the range of 3 to 5 instead of the standard power law value of 11/3. When the inner scale and outer scale are set to zero and infinity, respectively, this spectral model is reduced to the classical non-Kolmogorov spectrum.
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Generalized modified atmospheric spectral model for
optical wave propagating through
non-Kolmogorov turbulence
Bindang Xue,1,* Linyan Cui,1Wenfang Xue,2Xiangzhi Bai,1and Fugen Zhou1
1School of Astronautics, Beihang University, Beijing 100191, China
2Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
*Corresponding author: xuebd@buaa.edu.cn
Received September 14, 2010; revised March 17, 2011; accepted March 18, 2011;
posted March 18, 2011 (Doc. ID 134399); published April 29, 2011
A new generalized modified atmospheric spectral model is derived theoretically for wave propagating through
non-Kolmogorov turbulence, which has been reported recently by increasing experimental evidence and theore-
tical investigation. The generalized, modified atmospheric spectrum considers finite turbulence inner and outer
scales and has a spectral power law value in the range of 3 to 5 instead of the standard power law value of 11=3.
When the inner scale and outer scale are set to zero and infinity, respectively, this spectral model is reduced to the
classical non-Kolmogorov spectrum. © 2011 Optical Society of America
OCIS codes: 010.1290, 010.1300, 010.1330.
1. INTRODUCTION
Turbulence remains an important unsolved problem in phys-
ics and engineering, such as in pipe flow, aeronautics, and
meteorology [1]. Atmospheric turbulence is one of the most
important examples of turbulence, which has a significance
degrading impact on the quality of imaging and laser commu-
nication systems [24]. Traditionally, the performances of
imaging and laser communication systems are estimated with
the assumption that the turbulence is of the Kolmogorov type
and the Kolmogorov spectral model is applied mainly for
mathematical simplicity [5]. Nonetheless, the Kolmogorov
spectral model is theoretically valid only in the inertial sub-
range. When it is used to estimate the performance of imaging
and laser communication systems, it is ordinarily extended to
all ranges by assuming the inner scale size is zero and the out-
er scale is infinity. Several mathematically convenient turbu-
lence spectra with specific inner and outer scale have been
proposed, such as the Tatarskii, von Karman, and exponential
[5] spectra. Strictly speaking, these spectral models have the
correct behaviors only in the inertial range and are commonly
used for theoretical studies on optical wave propagation. The
Hill spectrum [6,7], however, can characterize the high fre-
quency enhancement property in the spectrum measured
by the experimental data [1], but has an awkward form for
theoretical studies. Compared with other turbulence spectral
models, the modified atmospheric spectrum of Andrews [8]is
the only analytical spectrum featuring a high wave number
bumpjust prior to the onset of the dissipation range that
has been observed in experimental data and also has a
convenient analytical form for theoretical studies. However,
it was developed for Kolmogorov turbulence with a specific
power law value of 11=3, and cannot be directly applied in
non-Kolmogorov turbulence cases.
In the past decade, both the experimental data [912]
and theoretical investigations [1315] have exhibited
non-Kolmogorov turbulence spectra in certain portions of
the atmosphere. Many applications [1618] have proposed a
non-Kolmogorov spectrum with a variable power law value
in the range of 3 to 5 instead of the standard power law value
of 11=3for Kolmogorov turbulence. In addition, a variable
amplitude factor has been proposed instead of a constant
value of 0.033. This modification still has the same problem
as the Kolmogorov spectrum. To handle non-Kolmogorov at-
mospheric turbulence, some theoretical spectral models were
developed, such as the generalized von Karman spectrum [19]
and the generalized exponential spectrum [20], which consid-
er finite turbulence inner and outer scales and have general
spectral power law values in the range of 3 to 5 instead of
the standard power law value of 11=3. The turbulence spectra
considered in this study are listed in Table 1, which gives a
clear description of these spectra.
In this study, the modified atmospheric spectral model
[8] is generalized to apply in non-Kolmogorov atmospheric
turbulence. The generalized modified atmospheric spectrum
considers finite turbulence inner and outer scales and has a
general spectral power law value in the range of 3 to 5 instead
of the standard power law value of 11=3.
2. MODIFIED ATMOSPHERIC SPECTRUM
Modified atmospheric spectrum is a turbulence spectral mod-
el that considers the influence of finite inner and outer scales,
and is given by [8]
ΦnðκÞ¼0:033C2
nκ11=31expκ2
κ2
01þa1·κ
κlb1
·κ
κl7=6expκ2
κ2
lð0k<Þ;ð1Þ
where C2
nrepresents the refractive-index structure parameter
for Kolmogorov turbulence and has the unit of m2=3,κis the
912 J. Opt. Soc. Am. A / Vol. 28, No. 5 / May 2011 Xue et al.
1084-7529/11/050912-05$15.00/0 © 2011 Optical Society of America
spatial wave number, a1¼1:802,b1¼0:254,κl¼3:3=l0,
κ0¼C0=L0,l0, and L0are the turbulence inner and outer
scale, C0is chosen differently depending on the application,
and, because the outer scale itself is not well defined, it is
difficult to assign any particular constant C0with outer scale
parameter κ0. In this study, we set C0¼4πjust as in [8].
In order to include both inner scale and outer scales ef-
fects, the generalized spectra recently adopted have the form
as [17,19,2123]
Φnðκ;αÞ¼AðαÞ·^
C2
n·Fðk; l0;L
0;αÞð0κ<;3<α<5Þ;
ð2Þ
where AðαÞis a constant that maintains consistency between
the refractive-index structure function and its power spec-
trum and ^
C2
nis the generalized refractive-index structure con-
stant (with units of m3α, when α¼11=3, with units of m2=3).
Physically, it is a measure of the strength of the fluctuations in
the refractive index and the behavior of ^
C2
nat a point along the
propagation path can be deduced from the temperature struc-
ture function obtained from point measurements of the mean-
square temperature difference of two fine wire thermometers.
Fðk; l0;L
0;αÞis the function that includes the influence of
finite inner and/or outer scale, and has different forms for
different spectra [17,19,2123].
To generalize the modified atmospheric spectral model for
non-Kolmogorov atmospheric turbulence, κ11=3in Eq. (1)
should be replaced by καand, by using Eq. (2), the general-
ized modified atmospheric spectrum becomes
Φnðκ;α;l
0;L
0Þ¼^
AðαÞ·^
C2
n·Fðk; l0;L
0;αÞ
¼^
AðαÞ·^
C2
n·κα·fðk; l0;L
0;αÞ
ð0κ<;3<α<5Þ;ð3Þ
fðκ;l
0;L
0;αÞ¼1expκ2
κ2
01þa1·κ
κlb1
·κ
κl7=6expκ2
κ2
l;ð4Þ
where ^
AðαÞhas the same meaning as AðαÞ,κl¼cðαÞ=l0,
κ0¼C0=L0, and cðαÞis the scaling constant.
In the next section, the expression forms of ^
AðαÞand cðαÞ
will be derived.
3. REFRACTIVE-INDEX STRUCTURE
FUNCTION FOR GENERALIZED MODIFIED
ATMOSPHERIC SPECTRUM MODEL
The refractive-index structure function DnðR; αÞdescribes the
behavior of the correlations of turbulence refractive-index
field fluctuations between two given points separated by a dis-
tance R. For three-dimensional Kolmogorov turbulence, the
relationship between DnðRÞand ΦnðκÞcan be described as [5]
DnðRÞ¼8πZ
0
κ2·ΦnðkÞ·1sin κR
κRdκ:ð5Þ
For non-Kolmogorov turbulence, the relationship between
DnðRÞand ΦnðκÞis
DnðR; αÞ¼8πZ
0
κ2·Φnðk; αÞ·1sin κR
κRdκ:ð6Þ
Substituting Eq. (3) into Eq. (6), and setting L0to infinity [this
will be explained after Eq. (13)], gives following expression:
DnðR; αÞ¼8πZ
0
κ2α·^
AðαÞ·^
C2
n
·1þa1·κ
κlb1·κ
κl7=6expκ2
κ2
l
·1sin κR
κRdκð7Þ
By expanding 1sin κR
κRwithin a Maclaurin series [24],
1sin κR
κR¼X
n¼1
ð1Þn1
ð2nþ1Þ!κ2nR2n;ð8Þ
and inserting it into Eq. (7), then interchanging the order of
series summation and integration, Eq. (7) becomes
Dn1ðR; αÞ¼8π·^
AðαÞ·^
C2
n·X
n¼1
ð1Þn1
ð2nþ1Þ!R2nZ
0
κ2αþ2n
×1þa1·κ
κlb1·κ
κl7=6expκ2
κ2
ldκ:ð9Þ
Using the gamma function ΓðxÞand hypergeometric function
1F1ða;b;zÞ[24] yields
Table 1. List of Some Atmospheric Turbulence
Spectraa
Type of Turbulence Styles of
Spectra
Spectra Inner
Scale
Outer
Scale
Kolmogorov turbulence (with
power law value of 11=3)
Most
simple
spectrum
Kolmogorov
spectrum
××
Analytical
spectra
Tatarskii
spectrum
p×
von Karman
spectrum
pp
exponential
spectrum
pp
Physical
spectra
Hill spectrum pp
modified
atmospheric
spectrum
pp
Non-Kolmogorov turbulence
(with power law value in the
range of 3 to 5)
Most
simple
spectrum
non-
Kolmogorov
spectrum
××
Analytical
spectra
generalized
von Karman
spectrum
pp
generalized
exponential
spectrum
pp
apand ×represent with or without considering the influence of a finite
inner/outer scale, respectively.
Xue et al. Vol. 28, No. 5 / May 2011 / J. Opt. Soc. Am. A 913
ΓðxÞ¼Z
0
κx1·eκdκðκ>0;x> 0Þ;
1F1ða;b;zÞ¼X
n¼0
ðaÞn·zn
ðbÞn·n!;ð10Þ
where ðaÞnis the Pochhammer symbol and has the form
ðaÞn¼ΓðaþnÞ
ΓðaÞ¼aðaþ1Þðaþn1Þ:ð11Þ
As a result, the refractive-index structure function in Eq. (9)
becomes
DnðR; αÞ¼4π^
AðαÞ^
C2
nκ3α
lΓα
2þ3
2
×11F1α
2þ3
2;3
2;R2κ2
l
4þa1·Γα
2þ2
×11F1α
2þ2;3
2;R2κ2
l
4b1·Γα
2þ25
12
×11F1α
2þ25
12 ;3
2;R2κ2
l
4:ð12Þ
For statistically homogeneous, isotropic, non-Kolmogorov
atmospheric turbulence, the related refractive-index structure
function is given by [8,19]
DnðR; αÞ¼^
C2
nlα5
0R2;0Rl0
^
C2
nRα3;l
0RL0
:ð13Þ
It should be mentioned that, because the random field of
index refractive fluctuation is nonisotropic for scale sizes
larger than the outer scale L0, no general description of the
refractive-index structure function can be predicted for
R>L
0. Consequently, in the derivation of refractive-index
structure functions for a generalized modified atmospheric
spectrum, L0is set to infinity for calculation purposes [8,19].
By using Eqs. (12) and (13), the unknown ^
AðαÞand cðαÞin
Eq. (3) will be derived next.
A. Expression Derivation of ^
Aα
When l0RL0, then R2κ2
l
4¼R2c2ðαÞ
4l2
0
1,1F1ða;b;xÞin
Eq. (12) can be expanded approximately for big arguments
and is given by [24]
1F1ða;b;xÞΓðbÞ
ΓðbaÞxaðx1Þ:ð14Þ
Substituting Eq. (14) into Eq. (12), DnðR; αÞ[see Eq. (12)]
becomes
DnðR; αÞ≈−4π^
AðαÞ^
C2
nΓα
2þ3
2
×Γð3=2Þ
Γðα=2Þ1
2α3
ðRÞα3ðl0RL0Þ:ð15Þ
By using Eqs. (15) and (13), and considering the properties of
the gamma function [24],
Γðαþ1Þ¼αΓðαÞ;Γð1αÞΓðαÞ¼ π
sinðπαÞ;
ΓðαÞΓðαþ1=2Þ¼212αffiffi
π
pΓð2αÞ:ð16Þ
As a result, ^
AðαÞcan be expressed with the form
^
AðαÞ¼Γðα1Þ
4π2sinðα3Þπ
2;ð17Þ
which has the same form in non-Kolmogorov spectral
models [16,17].
B. Expression Derivation of cα
When 0Rl0, then R2κ2
l
4¼R2c2ðαÞ
4l2
0
1,1F1ða;b;xÞin Eq. (12)
can be expanded for small arguments and is given by [24]
1F1ða;b;xÞX
1
n¼0
ðaÞn·zn
ðbÞn·n!¼1þa
bxðx1Þ:ð18Þ
By substituting Eq. (18) into Eq. (12), DnðR; αÞbecomes
DnðR; αÞπ^
AðαÞ^
C2
nκ5α
lR2·Γα
2þ3
23α
3þa1
·Γα
2þ24α
3b1
·Γα
2þ25
1225 6α
18  ð0Rl0Þ:ð19Þ
Using Eqs. (19) and (13), the expression of cðαÞcan be
derived:
cðαÞ¼π^
AðαÞΓα
2þ3
23α
3þa1
·Γα
2þ24α
3b1
·Γα
2þ25
1225 6α
18 1
α5:ð20Þ
4. GENERALIZED MODIFIED ATMOSPHERIC
SPECTRUM MODEL
By substituting Eqs. (17) and (20) into Eq. (3), we can obtain
the expression of the generalized modified atmospheric
spectral model. Figures 1(a) and 1(b) show ^
AðαÞand cðαÞ
as functions of α. When α¼11=3,^
Að11=3Þ¼0:033 and
cð11=3Þ¼3:25ð3:3Þ, Eq. (3) reduces to the modified atmo-
spheric spectrum [see Eq. (1)].
By setting the inner scale to zero and the outer scale to
infinity, the generalized atmospheric spectrum becomes
Φ0
nðκ;α;l
0;L
0Þ¼^
AðαÞ·^
C2
n·καð0κ<;3<α<5Þ;
ð21Þ
where ^
AðαÞhas the same form as in the non-Kolmogorov spec-
tral model [2123]. The generalized atmospheric spectrum
reduces to the non-Kolmogorov spectrum for the particular
case of zero inner scale and infinite outer scale.
914 J. Opt. Soc. Am. A / Vol. 28, No. 5 / May 2011 Xue et al.
Comparing the non-Kolmogorov spectrum [2123]to
Eq. (3) with zero inner and infinite outer scales gives
Φnðκ;α;l
0;L
0Þ
Φ0
nðκ;α;l
0;L
0Þ¼fðκ;l
0;L
0;αÞ;ð22Þ
where fðκ;l
0;L
0;αÞhas the same form as Eq. (4). Fig. 2shows
that the high frequency enhancement characteristics in the
generalized modified atmospheric spectra for power law
values of 10=3,11=3, and 3.9 are similar to the Kolmogorov
turbulence case (α¼11=3)[8].
Figure 2shows that the generalized modified atmospheric
spectrum is very close to the non-Kolmogorov spectrum in
inertial range for the inertial subrange (1=L0κ1=l0) with
an obvious high wave number bumpjust prior to the
dissipative range (κ1=l0) and then decreases markedly.
As shown in Fig. 2, a nonzero inner scale reduces values
of the spectrum at high wave numbers (κ>cðαÞ=l0) over
that predicted by the non-Kolmogorov spectrum, that is,
fðκ;l
0;L
0;αÞ<1. At low wave numbers (κ<C
0=L0), a similar
reduction in values of the spectrum is caused by the presence
of a finite outer scale.
The various power laws produce different effects on the
form of spectra. As αincreases, cðαÞdecreases, as seen in
Fig. 1(b),soκl¼cðαÞ=l0also decreases. Because the bump
position depends on the value of κl, it shifts to a smaller spatial
wave number position.
5. DISCUSSION AND CONCLUSIONS
In the modified atmospheric spectral model [8], the ½1þa1·
ðκ
κlÞb1·ðκ
κlÞ7=6component of Eq. (1) characterizes the high
Fig. 1. AðαÞand cðαÞas functions of α. (a) AðαÞ; (b) cðαÞ.
Fig. 2. (Color online) Scaled generalized modified atmospheric spectrum as a function of spatial wave number with a logarithmic scale (L0¼2m,
l0¼1mm).
Xue et al. Vol. 28, No. 5 / May 2011 / J. Opt. Soc. Am. A 915
frequency enhancement in Kolmogorov turbulence, and the
coefficients a1,b1, and 7=6present in the modified spectrum
were chosen by fitting a curve to the Hill numerical spectrum
[7], which has the form
ΦnðκÞ¼0:033C2
nκ11=3fexpð1:29κ2l2
0Þþ1:45
× exp½0:97ðln κl00:452Þ2g ð0k<Þ;ð23Þ
where the part of f·gthat describes the bumpcharacter
of the spectrum has a complex form. In fact, the Hill spectrum
is the solution to a second-order linear homogeneous differ-
ential equation:
d
dκκ14=3½ð13:9κηÞ3:8þ10:175 d
dκΦnðκÞ¼14:1κ4η4=3ΦnðκÞ:
ð24Þ
It is derived from the temperature differential equation [6]
d
dκHðκÞd
dκΦTðκÞ¼2Dκ4ΦTðκÞ;ð25Þ
where HðκÞ¼ð3=11Þβ1ε1=3κ14=3½ðκ=κþÞ2bþ11=ð3bÞ.κþ¼
0:072=ηand b¼1:9.κþparameterizes the position and b
parameterizes the width of the transition between the inertial
convective range and the viscous-convective range. The
choice of these two parameters arises from comparing the
model with the experimental data for Kolmogorov turbulence
case.
In this study, when we analyze the spectral enhancement
of the generalized modified spectrum in non-Kolmogorov
turbulence, we assume κþand bare unchanged. Although
Kolmogorov turbulence can be regarded as a special case
of non-Kolmogorov turbulence, physically, κþand bshould
be reevaluated, and these two parameters should take differ-
ent values for different α(3<α<5). Accordingly, the coeffi-
cients a1,b1, and 7=6in the generalized modified atmospheric
spectrum model should depend on experimental results.
However, with the limitations imposed by experimental
measurements, it is challenging to acquire sufficient data in
the troposphere and stratosphere to refine these parameters.
Consequently, the theoretical results presented in this study
will need to be justified by future experimental data.
ACKNOWLEDGMENTS
This work is partly supported by the United Fund Foundation
of the Civil Aviation, the National Natural Science Foundation
of China (NSFC, No. 60832011), and the Aeronautical Science
Foundation of China (20080151009).
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916 J. Opt. Soc. Am. A / Vol. 28, No. 5 / May 2011 Xue et al.
... The GMAS [9] for refractive index fluctuations is given by ...
... (x ) is the Euler gamma function. The constants a = 1.802, b = 0.254, and β = 7/6 are adopted from [9]. ...
... In the following, we set metric units of distance equal to pixel unit lengths in order to compare set covariances with covariances between voxel pairs resulting from error propagation [Eq. (9)]. ...
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In this paper, an approach for 3D noise generation is presented. The proposed algorithm might be a useful tool for the generation of correlated phase screens. These phase screens can be used for the simulation and modeling of optical wave propagation through atmospheric turbulence. Arbitrary user-defined covariance functions between voxel pairs can be achieved. Correlated 3D noise is formed by superposition of multiple uncorrelated 3D Gaussian noise patterns. These uncorrelated input noise patterns are of different dimensions. They are upsampled to the same target dimensions by linear interpolation. Each input pattern then contributes to total covariance on different spatial scales. The covariances between different voxels are expressed analytically by propagation of error. For a subset of randomly chosen voxels in the entire voxel space, relative deviations between the analytical and user-defined covariances are calculated. A sum of squares of these relative deviations is then minimized by machine learning methods. The optimized parameters are the weighting factors of individual uncorrelated 3D noise patterns. Corresponding covariance functions are numerically evaluated for two current atmospheric turbulence spectra. The first one is the generalized modified atmospheric spectrum. The second one is the generalized modified von Karman spectrum. Based on these covariance functions, optimal superpositions are calculated. Finally, statistical properties of these patterns are validated by ensemble sample covariance analysis.
... where ρ 0 represents the coherence length of a spherical wave propagating through non-Kolmogorov maritime atmospheric turbulence that is given by [15]; [30]; [36]. ...
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This study explores the propagation properties of orbital angular momentum (OAM) carried by a vector anomalous vortex beam (VAVB) in maritime atmospheric turbulence, utilizing the Rytov approximation. A comparative analysis is conducted between the VAVB and Laguerre-Gaussian beam, revealing that the VAVB exhibits a higher detection probability under speci fi c circumstances. This suggests that the VAVB is more suitable for scenarios where maximizing detection probability is critical. The detection probability of the signal OAM mode is affected by the characteristics of maritime atmospheric turbulence and propagation distance, but can be signi fi cantly improved by manipulating beam parameters such as wavelength, beam order, beam waist, and quantum number, while considering the characteristics of maritime atmospheric turbulence. Hence, the use of VAVB has the potential to facilitate reliable optical communication in challenging maritime environments.
... This establishes a relation between the phase fluctuation and the power spectral density Φ(κ). In our simulations, we choose the modified von Kármán spectrum, which takes both the influence of an inner and outer scale into consideration [25,26]. The modified von Kármán spectrum could be described as ...
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... Now, we modify Eq. (1) to a non-Kolmogorov spectrum. Following the modification in atmospheric optics [31,32,43], we add two adaptive functions A (α i ) and h (α i , c i ) to Eq. (1), ...
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Light propagation in turbulent media is conventionally studied with the help of the spatio-temporal power spectra of the refractive index fluctuations. In particular, for natural water turbulence several models for the spatial power spectra have been developed based on the classic, Kolmogorov postulates. However, as currently widely accepted, non-Kolmogorov turbulent regime is also common in the stratified flow fields, as suggested by recent developments in atmospheric optics. Until now all the models developed for the non-Kolmogorov optical turbulence were pertinent to atmospheric research and, hence, involved only one advected scalar, e.g., temperature. We generalize the oceanic spatial power spectrum, based on two advected scalars, temperature and salinity concentration, to the non-Kolmogorov turbulence regime, with the help of the so-called "Upper-Bound Limitation" and by adopting the concept of spectral correlation of two advected scalars. The proposed power spectrum can handle general non-Kolmogorov, anisotropic turbulence but reduces to Kolmogorov, isotropic case if the power law exponents of temperature and salinity are set to 11/3 and anisotropy coefficient is set to unity. To show the application of the new spectrum, we derive the expression for the second-order mutual coherence function of a spherical wave and examine its coherence radius (in both scalar and vector forms) to characterize the turbulent disturbance. Our numerical calculations show that the statistics of the spherical wave vary substantially with temperature and salinity non-Kolmogorov power law exponents and temperature-salinity spectral correlation coefficient. The introduced spectrum is envisioned to become of significance for theoretical analysis and experimental measurements of non-classic natural water double-diffusion turbulent regimes.
... Now, we modify Eq. (1) to a non-Kolmogorov spectrum. Following the modification in atmospheric optics [31,32,43], we add two adaptive functions A (α i ) and h (α i , c i ) to Eq. (1), ...
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Light propagation in turbulent media is conventionally studied with the help of the spatio-temporal power spectra of the refractive index fluctuations. In particular, for natural water turbulence several models for the spatial power spectra have been developed based on the classic, Kolmogorov postulates. However, as currently widely accepted, non-Kolmogorov turbulent regime is also common in the stratified flow fields, as suggested by recent developments in atmospheric optics. Until now all the models developed for the non-Kolmogorov optical turbulence were pertinent to atmospheric research and, hence, involved only one advected scalar, e.g., temperature. We generalize the oceanic spatial power spectrum, based on two advected scalars, temperature and salinity concentration, to the non-Kolmogorov turbulence regime, with the help of the so-called "Upper-Bound Limitation" and by adopting the concept of spectral correlation of two advected scalars. The proposed power spectrum can handle general non-Kolmogorov, anisotropic turbulence but reduces to Kolmogorov, isotropic case if the power law exponents of temperature and salinity are set to 11/3 and anisotropy coefficient is set to unity. To show the application of the new spectrum, we derive the expression for the second-order mutual coherence function of a spherical wave and examine its coherence radius (in both scalar and vector forms) to characterize the turbulent disturbance. Our numerical calculations show that the statistics of the spherical wave vary substantially with temperature and salinity non-Kolmogorov power law exponents and temperature-salinity spectral correlation coefficient. The introduced spectrum is envisioned to become of significance for theoretical analysis and experimental measurements of non-classic natural water double-diffusion turbulent regimes.
... κ l α is the inner scale wavenumber parameter defined by [22] κ l α 1 l 0 ...
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Optical scintillometers used to characterize turbulence are based on assumptions of isotropic, Kolmogorov turbulence following a κ − 11 / 3 spectral power law. However, experimental data suggest that the turbulence may at times be anisotropic and non-Kolmogorov. In this work, consideration is given to converting from the structure function constant, C n 2 , based on isotropic, Kolmogorov statistics to its generalized anisotropic, non-Kolmogorov form, C ˜ n 2 , for point receiver and large-aperture receiver scintillometers. It is found that C ˜ n 2 is dependent not only on power law and anisotropy parameters but that it is also a function of inner scale. The large-aperture scintillometer is found to be less sensitive to power law and inner scale than the point-aperture receiver. The optical parameters of two-fielded scintillometers are modeled as practical examples of these behaviors.
... The generalized von K arm an spectra, Eqs. (6) and (7), allow us to consider sound propagation through non-Kolmogorov turbulence, 15,16 which can result, for example, from intrinsic intermittency. [17][18][19] C. Non-dimensional, normalized spectra Reference 14 introduces the non-dimensional, normalized spectra of the temperature and velocity functions, respectively, ...
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The Markov approximation significantly simplifies formulations for the statistical moments of a wave propagating in a random medium. For the phase fluctuations, the Markov approximation is expected to be valid if the propagation range is much greater than the scale of largest inhomogeneities in a medium. In the atmospheric boundary layer, this scale can be several hundred meters, indicating that the Markov approximation might be inapplicable for relatively small ranges. In this paper, using geometrical acoustics, the correlation function and variance of the phase fluctuations of a plane sound wave are calculated without the Markov approximation and compared to previous results based on this approximation. The mean sound field and the spatial mutual coherence function (MCF) are also analyzed by expressing them in terms of the phase fluctuations. It is shown that for ranges smaller than the scale of largest inhomogeneities, the variance of the phase fluctuations is significantly smaller than that found with the Markov approximation. For large ranges, the relative difference between the two results tends to zero, while the absolute difference remains constant and can be much greater than unity. For the MCF, the Markov approximation is valid for both small and large ranges.
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Based on the generalized modified spectral model for non-Kolmogorov atmospheric turbulence, analytical expression for the spiral spectrum of Laguerre-Gaussian beam with orbital angular momentum propagating through a slant non-Kolmogorov turbulence channel has been derived. The average capacity of wireless optical links using Laguerre-Gaussian beam carrying orbital angular momentum in former channel is obtained. The effects of atmospheric conditions and beam parameters on average capacity are numerically demonstrated and analyzed in detail. It is shown that, the average capacity under generalized modified spectral model decreases 37.01% of the original value, which is the most rapidly than those of generalized von Karman spectrum (13.85%) and generalized exponential spectrum model (33.36%) for the same propagation distance z=1km, which should be considered in the realistic optical links.
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We investigated the spatial structure of atmospheric turbulence at Maui Space Surveillance Site (MSSS) using a 3.6 m telescope and a spatial filtering receiver. This receiver simultaneously records four star images on one camera frame. The star images are formed through pupil masks representing aperture diameters of 0.1 m, 0.5m, 1.5 m, and 3.6 m. We determined the camera orientation for each data set by moving the telescope at a given angle in azimuth and elevation. We calculated the horizontal and vertical components of the image centroid and evaluated the statistics of the horizontal and vertical wavefront tilt as a function of the aperture diameter and seeing conditions. We found several evidences of anisotropy of turbulence at MSSS. On four nights we observed that the variance of on-axis horizontal tilt exceeded the variance of the vertical tilt by a factor of 1.3-3.3. We believe that this is due to anisotropy of large-scale turbulence, where the horizontal scale of the turbulent inhomogeneities exceeds their vertical scale. The estimates of the horizontal and vertical turbulence outer scale confirmed this conclusion. In addition, in several data sets the horizontal image spot diameter of the long-exposure star image exceeded the vertical image spot diameter. We also found that large apertures are more likely to have higher anisotropy coefficient values than small apertures. This is because the contribution of small-scale isotropic turbulence to the image centroid reduces with increasing telescope diameter. In the case of isotropic turbulence, the power spectral densities (PSDs) of wavefront tilt are consistent with theoretical models. The telescope vibration modes were observed at 20 Hz. In the case of anisotropic turbulence, the PSDs of the horizontal tilt component have lower slope in the high frequency range, and difference between PSDs for large and small apertures is reduced. The anisotropy of turbulence and atmospheric tilt may affect the design and performance analysis of both active and passive optical systems.
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Free space laser system performance is limited by atmospheric turbulence that has been described for many years by Kolmogorov's power spectral density model because of its simplicity. Unfortunately several experiments have been reported recently that show Kolmogorov theory is sometimes incomplete to describe atmospheric statistics properly, in particular in portions of the troposphere and stratosphere. In this paper we present a Non-Kolmogorov power spectrum which uses a generalized exponent instead of constant standard exponent value 11/3 and a generalized amplitude factor instead of constant value 0.033. Using this new spectrum in weak turbulence, we carry out, for horizontal path, analysis of Long Term Beam Spread, Scintillation index, Probability of fade, mean SNR and mean BER as variation of the spectrum exponent.
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The effect of non-Kolmogorov stratospheric turbulence on star image motion is for the first time experimentally investigated with a ground-based telescope. A new approach permitting isolation of star image motion induced solely by atmospheric turbulence is employed. In this technique Polaris image wander is recorded with the telescope bolted in place to minimize uncontrolled telescope motion. High resolution temporal and spatial statistics of wave-front tilt are obtained. The dependencies of tilt variance, tilt power spectra, and tilt temporal correlation on telescope diameter are investigated for five apertures in the range 0.1-1.5 m. The experimental data show the dependence of tilt variance on telescope diameter does not follow the predictions of the Kolmogorov and von Karman models. The graph of the measured dependence has a "knee" which can be explained only by assuming a non-Kolmogorov stratospheric turbulence effect. The difference between tilt components in different axes indicates anisotropy in stratospheric turbulent inhomogeneities. The slopes of the measured tilt power spectra, approximately -1 in the low frequency range and -8/3 in the high frequency range, do not agree with theoretical predictions. The measured tilt temporal correlation scale is in the range 0.1-1.0 s, and the behavior of the correlation coefficients indicates the effect of large scale inhomogeneities not predicted by the conventional model. Uncontrolled telescope motion is manifested as a "bump" in the tilt power spectra in the range 70-90 Hz, but this makes an insignificant contribution to Polaris jitter variance.
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Atmospheric turbulence induces significant variation on the angle-of-arrival of laser beams used in free space laser communication. Angle-of-arrival fluctuations of an optical wave in the plane of the receiver aperture can be described in terms of the phase structure function that already has been calculated by Kolmogorov's power spectral density model. Unfortunately several experiments showed that Kolmogorov theory is sometimes incomplete to describe atmospheric statistics properly. In this paper, for horizontal path and weak turbulence, we carry out analysis of angle-of-arrival fluctuations using a non Kolmogorov power spectrum which uses a generalized exponent factor instead of constant standard exponent value 11/3 and a generalized amplitude factor instead of constant value 0.033. Also our non Kolmogorov spectrum includes both inner scale and outer scale effects.
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It is well know that free-space laser system performance is limited by atmospheric turbulence. Most theoretical treatments have been described for many years by Kolmogorov’s power spectral density model because of its simplicity. Unfortunately, several experiments have been reported recently that show that the Kolmogorov theory is sometimes incomplete to describe atmospheric statistics properly, in particular, in portions of the troposphere and stratosphere. We present a non-Kolmogorov power spectrum that uses a generalized exponent instead of constant standard exponent value 11 ∕ 3 , and a generalized amplitude factor instead of constant value 0.033. Using this new spectrum in weak turbulence, we carry out, for a horizontal path, an analysis of long-term beam spread, scintillation index, probability of fade, mean signal-to-noise ratio (SNR), and mean bit error rate (BER) as variation of the spectrum exponent. Our theoretical results show that for alpha values lower than α = 11 ∕ 3 , but not for alpha close to α = 3 , there is a remarkable increase of scintillation and consequently a major penalty on the system performance. However, when alpha assumes a value close to α = 3 or for alpha values higher than α = 11 ∕ 3 , scintillation decreases, leading to an improvement on the system performance.
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At present, system design usually assumes the Kolmogorov model of refractive index fluctuation spectra in the atmosphere. However, experimental data indicates that in the atmospheric boundary layer and at higher altitudes the turbulence can be different from Kolmogorov's type. In optical communications, analytical models of mean irradiance and scintillation index have been developed for a traditional Kolmogorov spectrum and must be revised for non-Kolmogorov turbulence. The image quality (resolution, MTF, etc.) is essentially dependent on the properties of turbulent media. Turbulence MTF must be generalized to include non-Kolmogorov statistics. The change in fluctuation correlations of the refractive index can lead to a considerable change in both the MTF form and the resolution value. In this work, on the basis of experimental observations and modeling, generalized atmospheric turbulence statistics including both Kolmogorov and non-Kolmogorov path components are discussed, and their influence on imaging and communications through the atmosphere estimated for different scenarios of vertical and slant-path propagation. The atmospheric model of an arbitrary (non-Kolmogorov) spectrum is applied to estimate the statistical quantities associated with optical communication links (e.g., scintillation and fading statistics) and imaging systems. Implications can be significant for optical communication, imaging through the atmosphere, and remote sensing. Bibtex entry for this abstract Preferred format for this abstract (see Preferences) Find Similar Abstracts: Use: Authors Title Abstract Text Return: Query Results Return items starting with number Query Form Database: Astronomy Physics arXiv e-prints
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Laser communication systems offer several advantages over conventional radio frequency (RF) systems but, because of shorter wavelength, are subject to various atmospheric effects. Particularly significant in this regard is the signal fading below a prescribed threshold value owing primarily to optical scintillations associated with the received signal. Over terrestrial paths of 1 - 3 km, or at large zenith angles between the transmitter and receiver in an uplink/downlink channel, the intensity fluctuations can easily exceed the limitations imposed by weak fluctuation theory. Under strong conditions the intensity fluctuations can no longer be modeled by a lognormal distribution - instead, we find the gamma-gamma distribution to be an excellent model over virtually all conditions of irradiance fluctuations. In this paper we discuss some recent advances in the modeling of optical scintillation under weak-to- strong fluctuations associated with both terrestrial links and satellite/ground links. The analysis presented here specifically addresses scintillation effects on detector signal-to-noise ratio (SNR) and on related fading probability and error probability or bit error rate (BER). We also discuss the use of multiple aperture receivers to mitigate the effects of optical turbulence.
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