Search NASA⌕ Search
Home/Archive/NASA NTRS

NASA NTRS · 20230016854

Artemis I Optical Navigation System Performance

Rebecca Inman·Greg Holt·John Christian·Kyle Smith·Christopher D'Souza
View original source ↗Export metadata ↓

Abstract

This paper summarizes the assessment of the Optical Navigation Flight Test Objective (FTO) during the flight of Artemis I. The Optical Navigation (OpNav) System was tested under a variety of range, target, and lighting conditions to evaluate the performance compared to the pre-flight predicted error models. In general, OpNav performed very well – successfully processing over a thousand images of starfields, Earth, and Moon. The performance of the algorithm when processing Moon images matched the pre-flight expected error models. The errors when processing Earth images were notably higher than the pre-flight models predicted, however this was found to be due to an over-estimation of the atmosphere bias used in the tuning of the algorithm. After the bias was re-tuned and the images reprocessed, performance significantly improved.

Explore related subjects

GNCOpNavArtemis IOptical Navigation

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Rebecca Inman, Greg Holt, John Christian, Kyle Smith, Christopher D'Souza. 2024-01-08. Artemis I Optical Navigation System Performance. https://ntrs.nasa.gov/citations/20230016854

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related reports

NASA NTRS2023

Backup Optical Navigation Attitude for Artemis-1 Backup Attitude Ground Tool

The Backup Optical Navigation Attitude (BONA) software was developed as a response to the Artemis1 Power Distribution Unit (PDU) hardware problems found early in 2021. The hardware problem, a capacitor installed incorrectly, removes the intended redundant path for which the PDU can relay its power and data to attached devices. Specific to the BONA context, the concern is that a failure of the single remaining path in this PDU would lead to an inability to communicate with one of the two-star trackers (STs) on Orion. By flight rule, being reduced to a single star tracker means an immediate turn around end-of-mission. The BONA software is not intended to extend the mission, but instead act as a single star tracker attitude confirmation tool. Insurance, if you will, for the Orion project that a ground tool is available to compare the single remaining ST results with optical navigation images retrieved during the mission. Engineers operating BONA in the Mission Control Center (MCC) Mission Evaluation Room (MER) will analyze the downlinked star field images and based on the stars identified and known time of image, derive vehicle attitude estimates, which can be compared with the ST results. Potentially, in extreme situations, and with expert recommendation, the derivations could lead to navigation state updates being commanded to Orion.

GNC↗
NASA NTRSDate not supplied

Streamlining GNC Architecture Development and FSW Integration forthe Mars Ascent Vehicle

The Mars Ascent Vehicle (MAV) will be the first vehicle to perform an ascent from the surface ofanother atmospheric planetary body outside of the Earth-Moon system. Significant light-time delayrequires complete autonomy of flight throughout ascent, and naturally a high level of reliability isdesired in both MAV’s hardware and software subsystems. The MAV Guidance, Navigation and Controls(GNC) team and the MAV Flight Software (FSW) team have partnered together to improve the efficiencyof algorithm integration onto the MAV flight processor, and to increase confidence that said integrationis successful and without human error. An interface architecture is proposed for the GNC suite thatallows both the guidance and navigation subsystems to provide code algorithms directly in C++, and thecontrols subsystem to provide MATLAB Simulink auto-coded algorithms. Several continuous integration/deployment (CI/CD) methodologies have been considered for ease of transition of algorithm code fromthe GNC team to the FSW team. The GNC/FSW teams also worked together to develop a cFS-friendlywrapper which abstracts the integration of the GNC algorithm code into an interface-level API that iscompatible with cFS. Several iterations of vehicle GNC code have been produced between the GNC/FSWteam’s partnership, and this strong interface between these two teams have allowed the GNC/FSWteams to greatly increase confidence of efficient and error-free implementation of the GNC code ontoMAV for a successful flight.

GNC↗
NASA NTRSDate not supplied

A Generalized Guidance Approach to In-Space Solid-Propellant Vehicle Maneuvers

Exploration-class vehicles that require fully autonomous ascent and descent must employ robust, explicit path-adaptive guidance algorithms that can operate in a wide range of physical environments. Vehicle designs that employ solid-propellant rocket motors (SRMs) for maneuvers are attractive from a systems engineering perspective because of their simplicity and reliability, but may cause complications for both mission designers and GNC engineers when dealing with total impulse uncertainty, as well as proper energy management of a motor with an uncontrolled cutoff time. This paper presents a simplified guidance algorithm, named Simple Cross-Product Steering (SxS), that was derived during early studies of NASA’s Mars Sample Return mission’s Mars Ascent Vehicle. The algorithm takes roots in a flight-proven guidance algorithm commonly referred to as Cross-Product Steering. SxS has been shown to provide sufficient guidance accuracy for in-space SRM burns in a simulated Martian environment, and preliminary studies have been conducted to test the algorithm in a solid-propellant lunar braking scenario. A method for predicting proper motor ignition time during execution of the Cross-Product Steering algorithm is the primary contribution of this paper. Mechanization notes are also provided that were realized in early phases of MAV. Results are shown for an example ascent vehicle in a simulated Mars environment.

GNC↗