Deep-space Risk Assessment for non-Gaussian Operations and Navigation

Advanced Space, LLC (Advanced Space) and Research Institution Utah State University (USU) propose fundamental enhancements to space traffic management beyond Earth’s orbit to augment NASA’s Multi-mission Automated Deep-space Conjunction Assessment Process (MADCAP). The deep-space regime is characterized by nonlinear dynamics and a sparsity of observations – both of which can cause linear, finite conjunction assessment assumptions to break down and Gaussian uncertainty representations to lose realism – which make it more challenging to maintain object state estimates and prevent an accurate evaluation of collision risk. The proposed solution features 1) enhanced uncertainty realism using Gaussian Mixture Model (GMM) and Directional State Transition Tensor (DSTT) propagation; 2) comprehensive collision risk quantification enabled by adding Probability of Collision (P_C) and Hamiltonian dynamics-based Mahalanobis distance metrics that use the enhanced uncertainty representations; and 3) a data-fusion catalog maintenance architecture that leverages non-traditional tracking techniques and autonomous onboard navigation that augments current ground tracking infrastructure. The proposed approach assesses existing non-traditional observational data sources to track debris and uncooperative satellites to extend current catalog maintenance capabilities. Part of the solution for the growing population of cooperative objects will require distributed catalog maintenance via autonomous onboard navigation techniques leveraging satellite-to-satellite tracking (SST) enabled by Advanced Space’s Cislunar Autonomous Positioning System (CAPS™). Advanced Space owns and operates the first commercial satellite operating at the Moon, CAPSTONE, which verified CAPS on orbit. Augmented tracking with CAPS will reduce the aggregate uncertainty of the object catalog and improve spaceflight safety.