Cislunar Uncertainty, Surveillance, Tracking, and Orbit Determination Evaluator (CUSTOD-E)

One of the significant technical challenges in space domain awareness is the accurate and consistent propagation of uncertainty for objects governed by highly nonlinear dynamics with stochastic excitation and uncertain initial conditions. This challenge is even greater in the xGEO region where three-body gravity becomes significant, resulting in the dynamics being more nonlinear. Additionally, the increased distance between an Earth-based sensor and the object reduces the apparent motion between them, resulting in little independent information to initialize an orbit. The initial uncertainties in xGEO orbits are therefore highly non-Gaussian, which inhibits the effectiveness of traditional propagation and filtering methods. Orbits within this area of regard enable low-cost options for spacecraft to rapidly alter course and threaten terrestrial and space-based assets. Being able to accurately understand and propagate the uncertainty of objects within this area is necessary to assess whether they pose a threat. In response to the DoD SBIR 2024.2 Solicitation for the Air Force Direct to Phase II Program, topic SF242-D022, Advanced Space proposes to develop a prototype uncertainty management software tool that matures existing internal analysis capabilities for tracking non-standard threats precisely in xGEO space. The proposed innovation builds upon significant Internal Research and Development (IRAD) investments made by Advanced Space, commercial work with NASA, research with IARPA in uncertainty propagation of millions of debris objects in low-Earth space regimes, and expertise in astrodynamics analysis and mission planning in xGEO. Advanced Space proposes to develop a methodology to characterize the uncertainty propagation of xGEO trajectories. We will identify uncertainty propagation behavior in the presence of a variety of mission profiles, evaluate uncertainty propagation across sensor exclusion and occultation geometries, and assess the impact of maneuvers in this space. We will also identify sensor network placement and tasking strategies to maximize information gain of xGEO objects and satisfy object custody requirements. Dr. Matthew Givens is the Principal Investigator (PI) for the proposed project, functioning as a Subject Matter Expert (SME) in space situational awareness (SSA). Dr. Givens earned his Ph.D. at the University of Colorado (CU) Boulder where he studied and researched novel relative navigation and mapping algorithms applied to SSA and spacecraft rendezvous and proximity operations. He is supported primarily by Dr. Nathan (Parrish) Ré, Principal Astrodynamics and Satellite Navigation (ASN) Engineer, who is an SME in low-thrust trajectory optimization and the use of neural networks for autonomous spacecraft operations. He is also supported by Mr. Justin Spurbeck, who is an experienced satellite operator, and researcher with focus areas in precision OD, GN&C, mission design, and astrodynamics in all space regimes.