Autonomous Navigation and Station-Keeping on Near-Rectilinear Halo Orbits

TL;DR

This paper presents an integrated optical navigation and station-keeping pipeline for near-rectilinear halo orbits, utilizing synthetic images, advanced filtering, and control schemes to improve spacecraft stability and reduce maneuver costs.

Contribution

It introduces a novel station-keeping approach combining synthetic image-based navigation, an improved targeting prediction with covariance integration, and a hysteresis mechanism for enhanced performance.

Findings

Filter performance varies with sensor field of view and measurement location.

Unscented transform-based prediction and hysteresis reduce station-keeping costs.

Cumulative ΔV depends on maneuver location due to orbit periodicity.

Abstract

This article develops an optical navigation (OPNAV) and station-keeping pipeline for the near-rectilinear halo orbit (NRHO) in high-fidelity ephemeris model dynamics, using synthetic images in a non-iterative horizon-based OPNAV algorithm, applying the result in a navigation filter, and using the obtained estimates in a station-keeping control scheme that keeps the spacecraft in the vicinity of a reference orbit. We study differential correction-based and minimization-based implementations of the so-called x-axis crossing control scheme, and propose an improved targeting prediction scheme by incorporating the filter's state covariance with an unscented transform. We also introduce a hysteresis mechanism, which improves station-keeping cost and provides insight into the difference in performance between the differential correction-based and minimization-based approaches. We perform Monte-Carlo experiments to assess the pipeline's tracking and {\Delta}V performances. We report several key findings, including the variability of the filter performance with the sensor field of view and measurement locations, station-keeping cost reduction achieved by the unscented transform-based prediction and hysteresis, as well as the variability of the cumulative {\Delta}V as a function of maneuver location due to the periodic structure in the OPNAV-based filter's estimation accuracy.