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On-board Limb-based Shape Modeling for Small Body Navigation

Missions to small bodies within our solar system are becoming more frequent. Generally, shape models of the target body are required to perform proximity operations as demonstrated by the OSIRIS-REx, Hayabusa2, and Rosetta missions. However, these missions required image downlinking to create high-resolution models on the ground. In some missions, especially small-sats, there may be data downlink data constraints, resulting in the inability to provide the large number of images needed for high-resolution shape models. A solution to this is the ability to generate shape models on-board during the approach to the target or initial proximity surveying. Current work implements a limb-based shape model routine that is able to be executed on a Raspberry Pi 1, which is similar to the processing capability to the flight computer on OSIRIS-REx, and that does not require low phase angle geometries. Initial shape model results generated from Bennu approach (Nov 2-3, 2018) show that the limb-based shape model agrees well with a 75-cm SPC shape model generated after Preliminary Survey; Results are: min difference -7.047m, max difference 17.347m, mean 1.122m, and RMS 3.219m. Further scenarios are presented herein.

Limb-based↗

Operational Performance of Limb-Based Navigation from Osiris-Rex at Bennu

During approach to an unvisited body, particularly small primitive bodies, much time is spent characterizing the target and learning how to navigate with respect to it. The primary means of navigating with respect to these bodies typically involves some form of optical navigation (OpNav), where observables are extracted from images of the target and fed to a navigation filter to refine the relative position and velocity between the spacecraft and the target. We demonstrate the performance of a recently developed, limb-based OpNav technique for the approach time period by applying it to flight data from the Origins, Spectral Interpretation, Resource Identification, and Security–Regolith Explorer (OSIRIS-REx) spacecraft’s approach to asteroid Bennu.

Andrew J. Liounis↗

Astrometric Reduction of Phoebe Using a Digital Shape Model

The Cassini Imaging Science Subsystem (ISS) has provided the most spectacular images of the Saturnian system [1] and these observations constitute a fundamental dataset of high accuracy and exceptionally long-time span for the purpose of astrometry [2]. Several elaborate astrometric efforts using Cassini ISS data have demonstrated their use for the development and maintenance of the Saturnian satellite ephemerides and have been critical in improving our understanding of their secular orbital evolution and interior properties[3].Astrometric efforts using images with well-resolved bodies often employ limb-based methods for center finding; this is proven to be robust for satellites with a uniform ellipsoidal shape. However, systematic biases are of concern for bodies that deviate considerably from tri-axial ellipsoids(e.g., moons with irregular shapes and/or extensive features such as craters, ridges, slumps and grooves). To help understand such biases, we used the Goddard Image Analysis and Navigation Tool (GIANT) [4,5]to improve the astrometric reduction of these moons. Here we apply the method to Phoebe (Saturn IX).

V Viswanathan↗

Celestial Navigation in Cislunar Space with autoNGC

Celestial navigation (CelNav) is a source of navigation observables where images of known solar system bodies are used to locate a spacecraft, beneficial within the solar system for both cislunar and deep space missions. CelNav provides a variety of design benefits to support and enable current and new autonomous space operations- using only a camera and a processor to produce in-situ measurements for navigation. This technology reduces subscription to ground-based tracking during all phases of a mission, freeing up resources for other operational needs. This also supports secure navigation since it eliminates the need for ground contact. CelNav enables missions where the light time delay between Earth and the spacecraft is too long (or the Earth to spacecraft line of sight is obscured) to support critical operations. It also enables smaller mission classes, where Deep Space Network (DSN)time is cost prohibitive, to reduce its cost by focusing primarily on data downlink. Finally, it enables the NASA Artemis program and other cislunar human space flight by providing redundant navigation to traditional radiometric tracking. In this presentation, we discuss the implementation of a CelNav app in autonomous Navigation, Guidance, and Control (autoNGC), a comprehensive flight software suite for onboard autonomy that is built on the core Flight System (cFS). The presentation also summarizes the results of flight software-in-the-loop (SIL) and processor-in-the-loop (PIL) demonstrations. Both are high-fidelity simulations with the use of a camera emulator hosted on a GPU server that simulates images that would be captured by the camera. The CelNav app leverages the use of cGIANT (cFS Goddard Image Analysis and Navigation Tool).Previously developed for the autoNGC software suite, cGIANT is an onboard autonomous image processing and optical navigation (OpNav) tool that performs limb-based OpNav and Terrain Relative Navigation. The added CelNav capability of cGIANT generates bearing measurements to multiple known celestial bodies (planets, moons, asteroids, comets, etc.) in monocular (2D) images. These observables are then fed to the Goddard Enhanced Onboard Navigation System (GEONS)navigation filter app, enabling us to navigate the spacecraft autonomously. In early 2025, the autoNGC CelNav capability is planned to be flight tested as part of the onboard autonomy experiment on the Cislunar Autonomous Positioning System Technology Operations and Navigation Experiment(CAPSTONE) spacecraft that is currently in a Lunar Near Rectilinear Halo Orbit(NRHO).

celestial navigation↗