In the realm of space exploration and energy, a team of researchers from the University of Colorado Boulder has made a significant contribution to understanding cislunar space—the region extending from geosynchronous altitudes to beyond the Moon. This team, led by Travis Yeager, includes Denvir Higgins, Peter McGill, Kerianne Pruett, Alexx Perloff, Tara Grice, and Michael Schneider, who collectively aim to advance our knowledge of this critical area for future space operations.
The researchers have released an open dataset containing one million high-fidelity cislunar trajectories, generated using the open-source Space Situational Awareness Python package (SSAPy). This dataset is designed to serve as a benchmark for developing methods in space domain awareness, navigation, and machine learning. It also acts as a reference library for statistical studies of orbit families and a foundation for community-driven extensions, such as exploring different time periods.
The dataset includes detailed information on the trajectories, taking into account high-degree Earth and Moon gravity, solar gravity, and Earth and Sun radiation pressure. While the model omits other planetary gravities for computational efficiency, it provides a comprehensive view of the cislunar environment. The trajectories are propagated for up to six years, starting from a single, fixed epoch, and the initial conditions are uniformly sampled from commonly used osculating-element ranges.
One of the key findings from this dataset is the observation of stability trends, such as a band near 5 GEO (Geostationary Equatorial Orbit) and the persistence of certain co-orbital classes, including L4/L5 librators. These observations are reported as descriptors of the dataset rather than new dynamical results. The primary contribution of this research is the scale, fidelity, organization, and open availability of the dataset, which lowers the barrier to comparative and data-driven studies in the cislunar regime.
For the energy sector, particularly companies involved in space-based solar power or satellite operations, this dataset offers valuable insights into the stability and behavior of objects in cislunar space. Understanding these trajectories can help in planning and optimizing satellite orbits, improving space domain awareness, and enhancing the overall efficiency and safety of space operations. The dataset’s open availability ensures that researchers and industry professionals can leverage this information to drive innovation and advancements in space-based energy solutions.
This research was published in the journal “Advances in Space Research,” providing a valuable resource for the scientific community and the energy industry alike.
This article is based on research available at arXiv.