Matthew Gilmartin
(Advisor: Prof. Dimitri N. Mavris)

will propose a doctoral thesis entitled,

Uncertainty-Based Methodology for the Development of Space Domain Awareness Architectures in Three-Body Regimes

On

Thursday, February 2nd at 10:00 a.m. EST
Conference room #304
Weber Space Science and Technology Building (SST II)

Abstract
The past decade has seen a massive growth in interest in lunar space exploration. An increase in global competition has led a growing number of countries and non-governmental organizations towards lunar space exploration as a means to demonstrate their industrial and technological capabilities. This increase in cislunar space activity and resulting increase congestion and conjunction events poses a significant safety impact to spacecraft on or around the moon. This risk was demonstrated on October 18th, 2021, when India’s Chandrayaan 2 orbiter was forced to maneuver to avoid a collision with NASA’s Lunar Reconnaissance Orbiter. In order to mitigate the safety impacts of increased congestion, enhanced space traffic management capabilities are needed in the cislunar regime. One foundational component of space traffic management is space domain awareness (SDA). Current SDA infrastructure, a network of earth-based and space-based sensors, was designed to track objects in near-earth orbits, and is not suitable for tracking objects in distant, non-Keplerian cislunar orbits. As a result, new infrastructure is needed to fill this capability gap.

The cislunar regime presents a number of challenges and constraints that complicate the SDA architecture design space. Unlike the near-earth regime, cislunar space is a three-body environment, violating many of the simplifying assumptions and models that are used in the near-earth domain. Furthermore, instability in cislunar dynamics means that state uncertainty plays a much more dominant role in system performance.

This research identified three gaps in existing design methods, exposed by the transition to the cislunar regime, that impede the ability of designers to explore the design space and perform many-query analyses like optimization. A new uncertainty-based methodology was then proposed to address these gaps and enhance design space exploration.

First, reliance on three-body dynamics violates analytic two-body models of spacecraft motion, meaning that cislunar trajectories must be numerically integrated at much greater computational cost.  A method was proposed that combines surrogate modeling techniques with and orbit family approach to develop an analytic parametric model of spacecraft motion. Second, reliance of most tracking filters on gaussian distributions creates convergence issues in non-linear domains such as the cislunar regime. This creates a need to characterize the realism of gaussian uncertainty approximations of non-gaussian uncertainty distributions. A modeling process is proposed for the development of models to characterize the realism of uncertainty estimates produced by tracking filters. Third, full-order cislunar SDA simulations suffer from exponential increases in computational cost as the number and diversity of systems in an SDA system increases. As a result, the computational cost of computing the detailed uncertainty produced by an SDA architecture is generally intractable in a many-query analysis context. A method wherein a reduced order model is developed to estimate the rate of information gain of information gain for individual sensor systems which is then aggregated for the overall architecture. A series of experiments were proposed to investigate the efficacy of the proposed methods in comparison to existing methods. Finally, a demonstration experiment was proposed, wherein the proposed uncertainty-based methodology was compared to a state-of-the-art methodology. The experiment proposes evaluating the same pair of design reference missions with each method and comparing the efficacy of the two approaches.

Committee

• Prof. Dimitri Mavris – School of Aerospace Engineering (advisor)
• Prof. John Christian – School of Aerospace Engineering
• Prof. Brian Gunter – School of Mechanical Engineering
• Dr. Greg Badura – Research Scientist, Georgia Tech Research Institute
• Dr. Alicia Sudol – Research Engineer, Aerospace Systems Design Laboratory