Detection and estimation of spacecraft maneuvers for catalog maintenance

TL;DR

This paper introduces a novel convex optimization-based method to detect and estimate maneuvers of space objects, improving catalog accuracy by recovering correlated observations despite unknown maneuvers and dynamics mismodeling.

Contribution

It presents a new approach for maneuver detection and estimation that does not require prior assumptions on thrust arcs or directions, enhancing catalog maintenance accuracy.

Findings

Successfully detects and estimates maneuvers from independent orbits.

Improves correlation recovery of observations for space object cataloging.

Operates without prior knowledge of thrust structure or direction.

Abstract

Building and maintaining a catalog of resident space objects involves several tasks, ranging from observations to data analysis. Once acquired, the knowledge of a space object needs to be updated following a dedicated observing schedule. Dynamics mismodeling and unknown maneuvers can alter the catalog's accuracy, resulting in uncorrelated observations originating from the same object. Starting from two independent orbits, this work presents a novel approach to detect and estimate maneuvers of resident space objects, which allows for correlation recovery. The estimation is performed with successive convex optimization without a-priori assumption on the thrust arcs structure and thrust direction.