Application of an Orbital GPR Model to Detecting Ground Ice and Deep Liquid Water Under the Mars Polar Cap

Statistics – Computation

Scientific paper

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0644 Numerical Methods, 0689 Wave Propagation (2487, 3285, 4275, 4455, 6934), 0933 Remote Sensing

Scientific paper

An important scientific objective in Mars exploration is to map the distribution and depth of the water/ice interface in the upper kilometers of the crust of Mars. Because environment uncertainties, such as the subsurface features and the ionosphere, will create ambiguity in the collected GPR data and also critically affect instrument performance, there is a compelling need for meaningful quantitative simulation of the planetary GPR problem. We have developed a model to simulate the complete planetary GPR problem to help bound data interpretation and instrument design. Parameters such as source bandwidth and power, surface and subsurface features, and ionospheric profiles can be rapidly iterated to understand their impact on GPR performance. Our model combines finite difference time domain (FDTD) and analytical methods and splits the computational volume into two pieces due to the large size of the simulation space. The near surface and subsurface fields are computed with the FDTD methods to improve the simulation flexibility of the surface and subsurface features such as rough surfaces and layer inhomogeneity. The two-way atmospheric and ionospheric propagation is treated with simpler but accurate plane-wave decomposition methods to maximize computational efficiency. We apply this model towards answering the question of whether key Martian polar subsurface targets are likely to be visible using orbital GPR. There are a number of obstacles to radar sounding of ground ice, deep liquid water and inter-glacial aquifers in the Martian polar subsurface, including signal losses from the ionospheric medium, subsurface ice conductivity, and reflective losses in the strongly layered subsurface. Using our planetary GPR model and the subsurface parameters converted from MGS/MOC images, we attempt to realistically assess the impact of all of these effects on the ability to detect these critical water-based features in the Martian polar subsurface.

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