Dielectric properties of the Martian south polar layered deposits: MARSIS data inversion using Bayesian inference and genetic algorithm

Details Dielectric properties of the Martian south polar layered deposits: MARSIS data inversion using Bayesian inference and genetic algorithm Dielectric properties of the Martian south polar layered deposits: MARSIS data inversion using Bayesian inference and genetic algorithm

May 2008

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2008jgre..11305004z&link_type=abstract

Journal of Geophysical Research, Volume 113, Issue E5, CiteID E05004

Computer Science

Sound

5

Planetary Sciences: Solid Surface Planets: Physical Properties Of Materials, Planetary Sciences: Solar System Objects: Mars, Planetary Sciences: Solid Surface Planets: Polar Regions, Planetary Sciences: Solid Surface Planets: Remote Sensing, Radio Science: Remote Sensing

Scientific paper

Mars Advanced Radar for Subsurface and Ionosphere Sounding (MARSIS) has offered abundant data, which have been used to estimate dielectric properties of the south polar layered deposits (SPLD) of Mars. This paper presents a new way to invert the data to estimate the dielectric properties of the SPLD. A total of 4364 measurements were analyzed. The received radar signals are controlled by the physical properties of the SPLD and its basal layer and in addition by a number of factors including the transmitted wave properties, the satellite height, and the atmosphere/ionosphere environments. The received signals may also be influenced by surface clutter. Most of these factors are variable. This complexity causes the inversion to be difficult. To carry out the inversion, it is therefore essential to define a reasonably simple model for the physics of the surface/subsurface layers where the radar signal is reflected. The top and bottom interfaces of the SPLD are observed by MARSIS as two reflection peaks of the radar signals. The intensity ratio between the two reflection peaks is observed to be a function of the time difference separating the two peaks. By modeling this dependency, the influences of the satellite position and the atmosphere/ionosphere environments are canceled. This is a major step toward carrying out the inversion. Nevertheless, the inverse problem remains ill-posed and highly nonlinear. Bayesian inference is employed to deal with the ill-posed aspect of the inversion, and genetic algorithm is introduced to deal with the nonlinearity. It is concluded that the most probable value of the relative dielectric constant of the SPLD lies in 3.0-5.0, conductivity 1.0-2.0 × 10-6 S/m, and the relative dielectric constant of the basal layer is 7.5-8.5 (The basal layer conductivity is assumed to be 1.0 × 10-7 S/m.) These results support a suggestion that the SPLD are water ice/dust mixtures with dust content varying from 0 to more than 75%.

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