Published on January 2, 2008
Electromagnetic Scattering Model Performance Assessment of the Global Ice Sheet Mapping Orbiter Concept: 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 AGU Fall meeting 2006, San Francisco, CA Dec 12th, 2006 (3) Dept. of Geological Sciences Ohio State University, USA (2) Dept. of Electrical Eng. and Computer Sci. University of Kansas, USA Slide2: Left Wing Right Wing Motivation Global Ice Sheet Mapping Orbiter (GISMO) First airborne SAR images of the base of the Greenland ice sheet: May 2006 Basal Return At Nadir Surface SAR Interferogram of the base 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. surface layers base noise 1.5 km image swath Slide3: Outline Outline Electromagnetic models for glaciers Physical Optics approximation Example simulations for nadiral observation Summary Goal: Preliminary formulation and evaluation of scattering model for interpreting GISMO images Slide4: Neglecting volume scattering, problem reduces to scattering from multi-layer rough surfaces (incl. ice, water and rock layers) Near Nadir Radar 500 m ~ 5 km unknown depth Interested in modeling both deterministic and stochastic surfaces Electromagnetic models EM Models 1-D surface profiles are considered here to simplify the analysis; methods also applicable to 2-D but requires more computation 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. surface base Slide5: 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 Slide6: 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) Slide7: Results Time-response along the profile 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. Exact Solution - MoM Approximate Solution - PO Slide8: Results (cont.) Thin layer of water 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 Surface profile: thin water Time response: MoM S = 0 ppt S = 2 ppt Slide9: Results (cont.) Local roughness Surface Profile with local roughness 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. Time response Slide10: 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 layer is 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.
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