A major finding in exploration of Mars is the indication that a large quantity of water has been present on Mars. To discover the distribution of this quantity of water, the Mars Express spacecraft is carrying a spaceborne radar sounder, called Mars Advance Radar for Subsurface and Ionospheric Sounding (MARSIS), in order to map Mars subsurface dielectric characteristics. The returned radar echoes from Mars will contain both surface and subsurface reflection components, but the part of the signal we are interested in is the reflected signal from subsurface layers. To retrieve these weak deep echoes from the radar signal, a signal processing algorithm needs to be developed. In this paper, we present a computationally efficient radar signal simulation based on the use of the Facet Method as a surface modeling scheme. This simulator will be used to validate the MARSIS ground processing software and to support the interpretation of MARSIS data. The first step in the simulation algorithm definition is to model the Mars surface. Many surface modeling methods have been developed and can be found in the literature, but considering the fact that Mars surface is very smooth, the modeling algorithm we have developed uses the Facet Method. In this paper, we show that the Facet Method is an efficient scheme for modeling a relatively smooth surface, such as the Mars' surface. The instrument simulation we define makes strict reference to the MARSIS radar parameters; however, it may be used to model any radar sounder.
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