Evaluation of Recent Measurements of Mercury’s Moments of Inertia and Tides Using a Comprehensive Markov Chain Monte Carlo Method
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Engineering topics
Publications and source records attributed to Stefano Bertone.
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We present new high-resolution topographic, illumination, and thermal models of Mercury’s 112 km-diameter north polar crater, Prokofiev. The new models confirm previous results that water ice is stable at the surface within the permanently shadowed region (PSR) of Prokofiev for geologic timescales. The largest radar-bright region in Prokofiev is confirmed to extend up to several kilometers past the boundary of its PSR making it unique on Mercury for hosting a significant radar-bright area outside a PSR. The near-infrared normal albedo distribution of Prokofiev’s PSR suggests the presence of a darkening agent rather than pure surface ice. Linear mixture models predict at least roughly half of the surface area to be covered with this dark material. Using improved altimetry in this crater, we place an upper limit of 26 m on its ice deposit thickness. The 1 km-baseline topographic slope and roughness of the radar-bright deposit are lower than the non-radar-bright floor although the difference is not statistically significant when compared to the non-radar-bright floor’s natural topographic variations. These results place new constraints on the nature of Prokofiev’s volatile deposit that will inform future missions, such as BepiColombo.
The LuNaMaps project seeks to advance mapping capabilities and understanding in preparation for lunar landing scenarios. In this presentation we outline the advancements made by the team over the last year.
The main contribution of this project is the combined knowledge of terrain relative navigation experts and lunar scientists who are familiar with both the lunar orbital imagery and the instruments that collected the data as well as how a TRN system utilizes map data. This knowledge comes in the form of published technical papers, benchmark map data sets, and software tools that can help others automate the process of creating the necessary maps for their own landing sites in the future. This document represents the project's plans to share all the lessons learned, processes developed, and applicable software tools with the public.
The main contribution of this project is the combined knowledge of terrain relative navigation experts and lunar scientists who are familiar with both the lunar orbital imagery and the instruments that collected the data as well as how a TRN system utilizes map data. This knowledge comes in the form of published technical papers, benchmark map data sets, and software tools that can help others automate the process of creating the necessary maps for their own landing sites in the future. This presentation provides a brief overview of the tools and processes developed by the project.
Both navigation and surface science can benefit from the ability to generate high resolution and accurate maps of the surface of the Moon and other solar system bodies. The primary way these maps are generated is through the use of orbital imagery and ranging data. Traditionally, the process of using orbital imagery and ranging data is tedious and labor-intensive. Additionally, once maps have been built, there has generally been limited effort in developing standards by which to verify the accuracy and quality of the generated maps. The Lunar Navigation Maps (LuNaMaps) project is a NASA Game Changing Development (GCD) project which over the last 4 years has aimed to address these issues both for the Moon and for other rocky solar system bodies. This has been accomplished through development of new and existing capabilities including: a suite of methods and tools to combine all sources of orbital imagery; a benchmark data set as well as basic requirements for high-fidelity simulations of precision landing functions; tools to synthetically enhance map products with lander-scale features for use in the development and testing of hazard detection systems; methods and tools to evaluate the accuracy of developed digital elevation maps (DEMs) and their quality for use in terrain relative navigation scenarios; and tools to realistically render image and lidar data. In this work, we provide an overview of the capabilities developed through LuNaMaps, demonstrating its use for processing existing lunar data, and describing how it can be applied to other use cases. We additionally provide preliminary results showing the application of the developed tools and processes to the generation of elevation maps of the Lunar Surface Proving Grounds (LSPG) lunar analog at Astrobotic’s Mojave testing facility using “orbital imagery” captured by a drone. In this terrestrial demonstration, we have the benefit of being able to compare the results to a ground truth model of the LSPG. We finally describe plans to use the newly created maps in a terrestrial terrain relative navigation demonstration over the LSPG in early 2025.
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