Monte Carlo Analysis of Low-Thrust Many-Revolution Spiral Out Trajectories with Statistical Errors for NASA's Gateway
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This work describes the development of a tool designed to analyze the impact of statistical error sources on low-thrust many-revolution trajectories, with a particular focus on application to NASA's Lunar Gateway. The impact of statistical errors (e.g. maneuver execution, orbit determination) is explored using Monte Carlo analysis to simulate many possible trajectories and understand their performance in specific measures of interest. Areas of concern include final state dispersions, eclipse avoidance and entry/exit uncertainties, and ground station pass timing uncertainty. The development of a Monte Carlo tool to analyze such trajectories is described and example results are shown to demonstrate how the tool works and how it will be used to help design operational strategies.



