Electromagnetic Scattering Model Performance Assessment of the Global Ice Sheet Mapping Orbiter Conc

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Electromagnetic Scattering Model Performance
Assessment of the Global Ice Sheet Mapping
Orbiter Concept

• N. Niamsuwan(1), J. T. Johnson(1), S. P. Gogineni
  (2) and K. C. Jezek(3)

(1) Dept. of Electrical and Computer Engineering
Ohio State University, USA
(2) Dept. of Electrical Eng. and Computer Sci.
University of Kansas, USA
(3) Dept. of Geological Sciences
Ohio State University, USA
AGU Fall meeting 2006, San Francisco, CA Dec
12th, 2006
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Motivation
Global Ice Sheet Mapping Orbiter (GISMO)
First airborne SAR images of the base of the
Greenland ice sheet May 2006
Right Wing

• 150 MHz air-borne radar, one array antenna on
  each wing.
• From an individual wing, SAR images can be
  produced. 2-D information basal reflectance
  maps.
• Both signals altogether are used to generate
  interferogram, providing 3-D information digital
  elevation models.

Left Wing
Basal Return At Nadir
Surface
1.5 km image swath
SAR Interferogram of the base
surface
layers
base
noise
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Outline
Outline
Goal Preliminary formulation and evaluation of
scattering model for interpreting GISMO images

• Electromagnetic models for glaciers
• Physical Optics approximation
• Example simulations for nadiral observation
• Summary

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Electromagnetic models
EM Models
surface

• Neglecting volume scattering, problem reduces to
  scattering from multi-layer rough surfaces
  (incl. ice, water and rock layers)

Near Nadir Radar
base

• Interested in modeling both deterministic and
  stochastic surfaces

• 1-D surface profiles are considered here to
  simplify the analysis methods also applicable to
  2-D but requires more computation

500 m 5 km

• Although GISMO operates at somewhat low
  frequencies, surface height variations of
  interest are on scales much larger than the EM
  wavelength.
• Near normal incidence geometry motivates
  examination of Physical Optics (PO) approximation
  plus extension to Geometrical Optics (GO) limit.

unknown depth
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Physical Optics Approximation
1-D surface
One interface problem
Fields on surface estimated using a local tangent
plane approximation
Multi-layer problems Neglecting multiple
interaction, we can cascade scattering effects
from each layer.
Using a plane wave spectrum approach,
deterministic PO theory involves a set of
transition matrices coupling incident and
scattered plane waves
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Example simulation
nadir observation
Surface Profile
Freq-response Time-response

• Permittivity of ice/pure water/rock labeled above
  (Debye formula/Malmberge and Maryott Model)
• Large scale surface domain split into 100m
  sections for analysis.
• For each 100m-surface, scattered fields versus
  frequency computed from 140-160 MHz.
• Fourier transform provides scattered field
  amplitude envelope versus time (0-sec delay
  0-meter height)

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Results
Time-response along the profile
Exact Solution - MoM
Approximate Solution - PO

• Bottom plots outline the rock (red) and water
  (blue) surfaces.
• PO solution is consistent with MoM note
  potential for observing weak scattering from
  basal rock even below pure water region
• Time resolution is limited by the bandwidth
  (20MHz) of the system.

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Results (cont.)
Thin layer of water
Surface profile thin water
Time response MoM
S 0 ppt

• As water layer becomes thinner, multiple
  interactions between interfaces can be observed
  (not captured in current PO model)
• However, for water with a slight salinity (2
  ppt), returns below water surface as well as
  multiple interactions vanish due to larger
  attenuation
• Detailed salinity properties of sub-glacier water
  an important issue

S 2 ppt
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Results (cont.)
Local roughness
Surface Profile with local roughness
Time response

• local-scale power-law (k-3 spectrum) roughness
  (rms height 1m) has been added to the base-rock
  profile.
• Time response due to 6 distinct surface
  realizations are shown on the right.
• Presence of local roughness affects both signal
  strength and range estimation.

• Dielectric contrast and roughness effects are
  dominant factor producing scattered field
  returns.

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Summary
Summary

• PO solution for (1-D) deterministic multi-layer
  surface implemented matches MoM well for assumed
  base surface properties
• Simulations show possibility of imaging sub-water
  layer rock if water layeris pure and relatively
  thin possibility of multiple reflections also
  shown.
• Sub-water effects eliminated if water is even
  slightly saline
• As expected, dielectric contrast (i.e. presence
  of water) and local large/small scale roughness
  determine scattering amplitudes observed
• Next steps
• - Ensemble averaging for stochastic surfaces
• - Formulation for 2-D surfaces
• - Apply to GISMO image interpretation.