System Level Analysis and Management of Orbital Debris Using Empirical Dynamic Modeling

TL;DR

This paper introduces a data-driven, complexity science-based method to analyze the system-level dynamics of orbital debris, aiding policy simulation with limited data.

Contribution

It presents a novel approach using shadow attractor reconstruction to understand and simulate orbital debris system dynamics.

Findings

Reconstructed a shadow attractor of orbital debris dynamics.

Enabled simulation of future debris scenarios based on policy changes.

Provided insights into the system-level implications of debris management.

Abstract

Orbital debris is a pressing problem which presents a danger to global space operations and a barrier to continued development of the space economy and space infrastructure. As research continues regarding orbital debris, there is a need for tools to understand the system-level implications of orbital debris solutions. This research considers the orbital debris problem as a dynamic process. Based on dynamic system theories, time-series variables of the numbers of orbital debris, orbital objects, and object launches should be causally linked, which means they share a common system attractor manifold. We propose a data-driven method based on complexity science to reconstruct a shadow attractor of the dynamic system using limited observable variables. The reconstructed shadow attractor helps us to understand the fundamental system dynamics for orbital debris and enables us to simulate the future of the orbital debris system based on changes to policy. These findings represent a significant advancement in our ability to understand high level impacts of space system policy with limited data available.