Interstellar Object Accessibility and Mission Design

TL;DR

This paper explores mission design and autonomous guidance for fast flyby missions to interstellar objects, emphasizing trajectory planning, navigation strategies, and future exploration readiness.

Contribution

It introduces a deep learning-based guidance algorithm and analyzes mission design considerations for rapid flybys of ISOs with velocities over 60 km/s.

Findings

Trajectory generation for synthetic ISOs demonstrates feasible mission profiles.

Autonomous navigation improves accuracy in fast flyby regimes.

Recommendations enhance preparedness for in situ exploration of ISOs and similar small bodies.

Abstract

Interstellar objects (ISOs) represent a compelling and under-explored category of celestial bodies, providing physical laboratories to understand the formation of our solar system and probe the composition and properties of material formed in exoplanetary systems. In this work, we investigate existing approaches to designing successful flyby missions to ISOs, including a deep learning-driven guidance and control algorithm for ISOs traveling at velocities over 60 km/s. We have generated spacecraft trajectories to a series of synthetic representative ISOs, simulating a ground campaign to observe the target and resolve its state, thereby determining the cruise and close approach delta-Vs required for the encounter. We discuss the accessibility of and mission design to ISOs with varying characteristics, with special focuses on 1) state covariance estimation throughout the cruise, 2) handoffs from traditional navigation approaches to novel autonomous navigation for fast flyby regimes, and 3) overall recommendations about preparing for the future in situ exploration of these targets. The lessons learned also apply to the fast flyby of other small bodies, e.g., long-period comets and potentially hazardous asteroids, which also require tactical responses with similar characteristics.