Computer Science – Sound
Scientific paper
Dec 2004
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2004agufm.p13a0985f&link_type=abstract
American Geophysical Union, Fall Meeting 2004, abstract #P13A-0985
Computer Science
Sound
0619 Electromagnetic Theory, 0634 Measurement And Standards, 0644 Numerical Methods, 0669 Scattering And Diffraction, 0689 Wave Propagation (4275)
Scientific paper
Low frequency sounding radars can probes the subsurface layers of a planetary surface down to varying depths depending on the sounding frequency, geometry, surface topography, geoelectrical and geomagnetic properties of the sounded terrains. Hence a good understanding of the electric and magnetic wave interaction mechanisms between the radar waves and the rocks and sediments constituting the investigated media is crucial for any future data analysis and interpretation. In this presentation we validate the use of a Finite Difference Time Domain algorithm adapted to simulate the radar wave interaction with complex geological model that take into account real topographic data and layer heterogeneities. The radar-backscattered echoes from some volcanic (cones, ashes and faults) and sedimentary features (dunes, fluvial and dry lake deposits) have been investigated at the frequency band from 1 to 100 MHz and compared to Ground Penetrating Radar field collected data at the same frequency band. In a first step the algorithm have been adapted to simulate the response of orbital sounding instruments (i.e.: MARSIS and SHARAD) and a monostatic GPR all dedicated to map the possible presence of subsurface water in the Martian permafrost. We also suggest some solutions for the clutter problems for orbital and future landing Ground Penetrating Radar on Mars. In a second step the algorithm is being validated for the case of Europe and the Moon. Results show that combining multiple low frequency sounding frequencies strongly reduces the ambiguities on the identification of subsurface water saturated interfaces and stratigraphy at different depths.
Fernandez Javier
Heggy Essam
Khan Sergiy
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