Information-Based Trajectory Planning for Autonomous Absolute Tracking in Cislunar Space

TL;DR

This paper presents an information-based trajectory planning method for autonomous satellite tracking in cislunar space, optimizing navigation performance with minimal ground intervention using a novel SCP approach.

Contribution

It introduces a new trajectory planning framework that maximizes information gain for autonomous satellite tracking in cislunar space, using mutual information and sequential convex programming.

Findings

Enhanced autonomous navigation in cislunar space.

Effective trajectory optimization balancing information gain and control effort.

Demonstrated improvements in satellite tracking accuracy.

Abstract

The resurgence of lunar operations requires advancements in cislunar navigation and Space Situational Awareness (SSA). Challenges associated to these tasks have created an interest in autonomous planning, navigation, and tracking technologies that operate with little ground-based intervention. This research introduces a trajectory planning tool for a low-thrust mobile observer, aimed at maximizing navigation and tracking performance with satellite-to-satellite relative measurements. We formulate an expression for the information gathered over an observation period based on the mutual information between augmented observer/target states and the associated measurement set collected. We then develop an optimal trajectory design problem for a mobile observer, balancing information gain and control effort, and solve this problem with a Sequential Convex Programming (SCP) approach. The developed methods are demonstrated in scenarios involving spacecraft in the cislunar regime, demonstrating the potential for improved autonomous navigation and tracking.