High performance computer simulations of the subsurface ... · of celestial bodies. Yaroslaw A....
Transcript of High performance computer simulations of the subsurface ... · of celestial bodies. Yaroslaw A....
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High performance computer simulations
of the subsurface radar location
of celestial bodies.
Yaroslaw A. ILYUSHIN
Moscow State University
Russia Moscow 119992 GSP-2 Lengory phone +7 (495) 939-3252
e-mail [email protected]
Institute of Radio-engineering and Electronics ulitza Mokhovaya, 11/7 125009 Moscow Russia phone 007 (495) 629-35-74
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What is beneath? Searching for the subsurface water
Earlier Nowadays
Dowsing
Ground penetrating radar (GPR)
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Deep subsurface sounding
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GPR space instruments:
the historical review
ALSE (Apollo 17, Moon)
MARSIS (Mars, Mars Express)
SHARAD (Mars, Mars Reconnaissance Orbiter)
LRS (Moon, Kaguya)
CONSERT radio wave sounder (ROSETTA, 67/P)
Planned now:
RIME (Jovian icy moons, JUICE)
REASON (Jovian icy moons)
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Small-scale irregularities
Diurnal surface
IONOSPHERE
Spacecraft
H H
H
Techniques of radar sounding
of the Solar system celestial bodies
1
2
ion
Subsurface features
Surface clutter
Ionospheric scattering
Ionospheric
dispersion
Aperture synthesis
Layered structures
Volume scattering
Earth
Landed rovers
IONOSPHERE
SURFACE
SUBSURFACE
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dtiHFFts ~exp2
1 *
Compressed signal after matched filtration
z
dzznk0
2 - systematic ionospheric phase shift
f 2 2
2
1
zzn
p , ][3392 32 mNp , c
k
,
~ - phase correcting function
H - spectral window function (Hanning)
UWB LFM signal processing
21221121
2121
2
2
2
1
2
~~exp
,2
1
ddti
HHFFts
Amplitude mean square (mean power) of the compressed UWB LFM signal
Two-frequency
correlation function
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Side echo
Surface Clutter (Side Reflections Coming From the Rough Surface)
Synthetic aperture
Rough surface
Nadir echo
Ionosphere
Two frequency correlation function
Gaussian height correlation function
2
2
2
22 exp
yx
yxhrrhrhr
0
2 expr
xhrrhrhr
Exponential height correlation function
where
Aperture synthesis Rough surface
Propagation
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Side clutter.
Two frequency correlation function evaluation
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Side clutter.
Two frequency correlation function evaluation
Spatial displacement between
synthetic aperture centers at two frequencies. For the step frequency radar (SFR) must be taken into
account
The synthetic aperture lengths can
be different at different frequencies and vary with the position of the spacecraft
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Anisotropic surface roughness
height correlation function
Compressed UWB LFM signals coming from rough front surface. Solid curves correspond to
x=1000 м, dashed curves - x=10000 м. For all signals y=1000 м. R.m.s. roughness
height deviation shown by numbers near each curve.
Gaussian correlation function
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z
RAZ
DPL Radar equation
PLAZ DRA
sAZ LzR 2/zcDPL 2Radar pulse length limited
diameter of the scattering
area
Azimuth resolution of the radar
Diffuse scattering area
Spacecraft
Rough surface reflection from the planet:
radar equation approximation
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Hagfors’ law: reflection from the rough surface
X Y
0
Exponential surface roughness height
correlation function
0
2 expr
xhrrhrhr
2324 sincos2
C
CRH
Scattering cross section of the unit area
Hagfors’ roughness parameter
222
2
0
2
16 h
rC
Normalized diffuse reflection power from the nadir
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Exponential height correlation function:
Hagfors’ law test
Peak amplitudes of the compressed UWB LFM signals vs. r.m.s. height of the roughness. Solid
black curves – amplitude calculation through the two frequency correlation function, dashed
colored curves – approximate estimation by the unit area scattering cross section (radar equation).
Height correlation functions are isotropic, correlation scales are shown near each pair of the curves
by numbers.
Specular reflection
Diffuse scattering
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Clutter simulation algorithm immediate evaluation of the Kirchhoff integrals
Input data
(Martian topography
from MOLA server)
Along-track interpolation
Across track
interpolation
on the regular grid
Triangulation
Integration over the
surface
with the kernel (3)
FFT
spectrum --> signal
Final result:
the radargram
For all
frequencies
For all
sub-satellite
points
of the track
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Kirchoff approximation:
facet surface model (SHARSIM etc.) Discontinuities produce artifact
echoes on simulation
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Kirchoff approximation:
we use surface triangulation
Surface is represented
by a continuous function
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MEX orbit 9466 (the southmost part)
MOLA topography data (above); mosaic of HRSC images
H5191_0000_ND3 and H7357_0000_ND3 (below)
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MEX 9466 orbit radargrams
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Anisotropic correlation function of the
ionospheric plasma fluctuations
Planetary surface
Synthetic aperture
Ionosphere (phase screen)
Anisotropic fluctuations
I II
x5,y5
x1,y1
x6,y6
x2,y2
x3,y3
x4,y4
z1
z2
z
y
x
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Anisotropic correlation function of the
ionospheric plasma fluctuations:
coherency function (I,II) Random phases
must be averaged all together
Synthetic aperture terms
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Ionospheric phase fluctuations:
effective phase screen model Correlation function of the
dielectric permittivity e
Integrated correlation function
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Random phase shift correlation coefficients
Phase shift characteristic function
(averaged exponent of all the random phase shifts) is
where
(we perform the Taylor series expansion in the bij)
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Two frequency correlation function
where
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Matrices of the Gaussian integrals
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Matrices of the Gaussian integrals
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Degradation of the compressed LFM UWB signals
due to anisotropic ionospheric scintillations
Samples of the simulated GPR signals distorted by the anisotropic ionospheric scintillations.
MARSIS BandIV (4.5–5.5MHz). Ionospheric layer thickness H = 15 km,
ionospheric plasma frequency fp0 = 4MHz. Plasma density fluctuations level DN/N=0.4%
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Anisotropic ionospheric fluctuations:
degradation and broadening
of compressed UWB LFM signals
Broadening of the compressed
UWB LFM signals’ peaks
Degradation of the amplitude of the
compressed UWB LFM signals
DN/N
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Non-stationary ionospheric fluctuations
(scintillations)
Non-stationary fluctuations
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Non-stationary ionospheric fluctuations:
Gaussian integrals matrices
Additional terms due to non-stationary effects
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Degradation of the compressed LFM UWB signals
due to non-stationary ionospheric scintillations
Samples of the simulated GPR signals distorted by the ionospheric scintillations.
MARSIS BandIV (4.5–5.5MHz). Ionospheric layer thickness H = 15 km,
ionospheric plasma frequency fp0 = 4MHz. Plasma density fluctuations level
DN/N=0.4%
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Non-stationary ionospheric scintillations:
degradation and broadening of compressed LFM signals
vLc - non-stationary correlation length (distance traveled by the spacecraft during the
characteristic period of the scintillations)
1%
2%
3%
4%
Peak amplitude degradation Pulse broadening at ~-50 dB
(correction for the amplitude
degradation is applied)
Correlation function of the plasma inhomogeneities is assumed to be isotropic
(x = y = ). Fluctuation levels DN/N are marked by green labels.
The peak amplitude is affected both by and Lc while only is responsible for
the peak broadening.
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Quasi-deterministic phase screen model
of the stochastic ionospheric fluctuations
Synthetic aperture
Ionosphere
Surface
Received field
Field propagation back from the spacecraft to the surface and back to the
satellite is described within the paraxial (Kirchoff) approximation
Aperture synthesis is approximately simulated by the integration with Gaussian
weight function
Ionospheric phase shift
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Numerical simulations
i
ii xkAx )cos(
...)exp(...)()()(
...))cos()cos()cos(exp(
332211321,..,,
...
332211
321321
321
xnikxnikxnikAJAJAJi
xkAxkAxkA
nnnnnn
nnn
We restrict our attention to the simple quasi-deterministic model of the
ionospheric stochastic phase fluctuations, which is essentially 1D superposition
of several sinusoidal components with phases and amplitudes
It can be shown that the following expansion of the phase shift is valid:
121
332224
1)()(
iz
k
iz
k
zdydxdydxRE
)()()()()()( 3213,,,,, 1 3213321321 221
321321 AJAJAJAJAJAJi mmmnmmmnnn nnn
mmmnnn
)22
)(
4
)(
4
)(2
22
)(exp(
1
2
3
1
2
3
133
2
2
32
2
2
32
222
1
2
2
1
2
21
z
kyi
z
xxkiikzxik
z
yyki
z
xxkiikzxikz
z
kyi
z
xxkiikz
where Jn(.) are the cylindrical Bessel functions of the first kind. Substituting this
expansion into the integral expression for the registered field, one gets
the representation for this field in the form of the discrete sum, which can be easily
evaluated with the computer:
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Obtaining of the registered field thus reduces to the evaluation of terms such that
)4
exp(det
)exp(
1BAB
AxdxBxxA
ij
T
ij
nn
iijiij
Variables of integration are separated into two groups (x- and y-), for which the matrix
Ai and the vector Bi respectively are
21
21
11
121
21
1
111
2
)(
4
)2(
42
44
)2(
2
22
1
zz
zzik
z
ik
z
ik
z
ik
zz
zzik
z
ik
z
ik
z
ik
z
ik
L
Ax
ij
3
2
2
0
)(
2
ik
ikL
xiL
Bx
i
21
21
2
221
21
)(
4
)2(
4
44
)2(
zz
zzik
z
ik
z
ik
zz
zzik
Ay
ij
0)( y
iB
We omit the intermediate calculations and reproduce the final result:
)()()()()()()( 321321
)(
3213121
321321 AJAJAJAJAJAJiE mmmnnn
mmmnnn
))(4
)()2)(()2))(2((exp(
21
2
21
2
0
2
32
2
123
2
3
2
2211
zzkL
zzixLLkkkLzkkkkzziz
where summation is performed over all six indices 321321 ,,,,, mmmnnn
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Dependence on the synthetic aperture length.
Strong phase fluctuations <2>=25 Moderate phase fluctuations <2>=4
The compressed UWB LFM signals with various synthetic aperture lengths, reflected from
the multi-layered subsurface structure, are shown in the figures. The longer the synthetic
aperture, the better is the suppression of diffracted peaks in the signals. Extension of the
synthetic aperture over the optimal length (half the Fresnel zone size at the central
frequency of the LFM band) does not lead to further growth of the suppression.
Front surface
reflection
Front surface
reflection
Subsurface
reflection
Subsurface
reflection
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Aperture synthesis vs. no aperture synthesis
Single pulse (no aperture synthesis) Aperture synthesis (optimal aperture length)
When stochastic phase fluctuations in the ionosphere are of moderate strength (r.m.s.
phase deviation does not exceed one whole period), synthetic aperture technique allows to
effectively suppress diffracted signals coming from side directions. When the phase
fluctuations are stronger than 2 r.m.s., the effect of the aperture synthesis rapidly
vanishes.
Front surface
reflection Front surface
reflection
Subsurface
reflection Subsurface
reflection
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Subsurface radargram profile: numerical simulation.
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orbital
monostatic bistatic
Z
X Y
Three schemes of radar sounding
of the Martian polar layered deposits
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t, ms
Dx, m
Dx
Schematic view
of the experiment
2D geometry
Bistatic radar sounding of the northern polar ice sheet
with the landed instrument.
2D model, LFM chirp band 2.5-3.5 MHz TE mode
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Surface and leaky waves:TE and TM mode
TE TM
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Dx, м Dx, м
t, ms t, ms
TE TM
Transverse magnetic (TM) mode demonstrates low reflections at large incidence
angles, in particular, close to the Brewster angle.
Dusty layers refractive index n=2.4
Bistatic radar sounding of the northern polar ice sheet
with the landed instrument.
2D model, LFM chirp band 10-15 MHz both TE and TM modes
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Bistatic radar sounding of the northern polar ice sheet
with the landed instrument.
3D model, LFM chirp band 10-15 MHz
Signal level calibration is arbitrary. Loss tangents of the dusty layers are shown by numeric labels.
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Conclusions and remarks
•The impact of the stochastic small-scale irregular structure
of the ionosphere on the performance of the orbital ground-
penetrating synthetic aperture radar (SAR) instrument is
considered.
•Several numerical models for the computer simulations of
the orbital ground-penetrating SAR experiment have been
implemented, tested and exploited.
•Different effects, caused by the plasma irregularities and
surface roughness, have been revealed and estimated
numerically.
•Applicability of the results to the GPR sounding data
validation and to the experimental radar studies of the
ionospheric irregularities has been discussed.
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