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Modeling cratered surfaces with real and synthetic terrain for testing planetary landers

The autonomous guidance of a spacecraft lander requires extensive testing to develop and prove the technology. Methods such as machine vision for navigation and both vision and LIDAR for hazard avoidance are being studied and developed to provide precise, robust lander guidance systems. A virtual test environment that can simulate these instruments is a vital tool to aid this work. When available, terrain elevation models can provide a base for simulation but they frequently contain artifacts, gaps, or may not have the required resolution. We propose novel techniques to model heavily cratered surfaces for testing planetary landers by combining crater models and fractal terrain to create a multiresolution mesh for simulating a spacecraft descent and landing. The synthetically enhanced models are evaluated by comparing enhanced terrain based on Clementine/RADAR data with higher resolution terrain models from the Selene and the Lunar Reconnaissance Orbiter (LRO) to show that the artificial models are suitable for testing planetary lander systems.