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RadLab: A Comprehensive Database and Graphical and Programming Interfaces for Space Radiation Data

RadLab, a component of the NASA Open Science Data Repository (OSDR), is a database of radiation measurements from multiple instruments and spacecraft that provides visual and programmatic interfaces for interrogation and retrieval of these data. The attributes of data available through RadLab include spacecraft, types of radiation sensing instruments, locations within the spacecraft (e.g. ISS modules), associated celestial bodies, trajectories, and spacecraft coordinates; the primary type of data is the absorbed dose rate, as well as flux and dose equivalent rate where available. The application programming interface (API) implements a request syntax for retrieval of timestamped data filtered by various combinations of such attributes; the graphical user interface (GUI) extends this functionality with visualizations (time series plots, comparison plots, geospatial visualizations) which provide easy means to assess data availability, iteratively refine search parameters, interactively inspect the data, and export target data subsets. Datasets are continuously being added to the RadLab database as part of the rolling release process. Investigators from multiple countries, including the US, Canada, Germany, Bulgaria, Hungary, Italy, Japan, Russia and the Czech Republic, have committed to provide data from their instruments in and beyond low Earth orbit. The current release contains datasets provided by US and international collaborators and includes readings from multiple modules of the ISS, the BioSentinel CubeSat, Chang’e 4, the Lunar Reconnaissance Orbiter, the ExoMars Orbiter, and the Curiosity rover. Datasets are associated with respective RadLab knowledgebase articles which include instrument descriptions and provide bibliographical references. RadLab aims to provide a comprehensive, dynamic compendium of space radiation data, enabling the scientific community to perform analyses of data from multiple detectors and to determine the radiation environment of research missions and experiments. Some of its applications include inference of absorbed radiation dose for NASA GeneLab payloads, and training predictive models as part of the 2024 FDL-X challenge. The platform is actively expanding and seeking additional data, with plans to also cover past (e.g. Shuttle, Mir) and future (e.g. Artemis) missions. The RadLab Working Group has been created to aid in this process as well as to foster collaborations among data contributors and users, to develop standards for data harmonization, and to guide the development of the platform, with the goal to establish the use of RadLab in space radiation research and to advance our understanding of the radiation environment in outer space.

Kirill Grigorev↗

RadLab: A Comprehensive Database and Graphical and Programming Interfaces for Space Radiation Data

RadLab, a component of the NASA Open Science Data Repository (OSDR), is a database of radiation measurements from multiple instruments and spacecraft that provides visual and programmatic interfaces for interrogation and retrieval of these data. The attributes of data available through RadLab include spacecraft, types of radiation sensing instruments, locations within the spacecraft (e.g. ISS modules), associated celestial bodies, trajectories, and spacecraft coordinates; the primary type of data is the absorbed dose rate, as well as flux and dose equivalent rate where available. The application programming interface (API) implements a request syntax for retrieval of timestamped data filtered by various combinations of such attributes; the graphical user interface (GUI) extends this functionality with visualizations (time series plots, comparison plots, geospatial visualizations) which provide easy means to assess data availability, iteratively refine search parameters, interactively inspect the data, and export target data subsets. Datasets are continuously being added to the RadLab database as part of the rolling release process. Investigators from multiple countries, including the US, Canada, Germany, Bulgaria, Hungary, Italy, Japan, Russia and the Czech Republic, have committed to provide data from their instruments in and beyond low Earth orbit. The current release contains datasets provided by US and international collaborators and includes readings from multiple modules of the ISS, the BioSentinel CubeSat, Chang’e 4, the Lunar Reconnaissance Orbiter, the ExoMars Orbiter, and the Curiosity rover. Datasets are associated with respective RadLab knowledgebase articles which include instrument descriptions and provide bibliographical references. RadLab aims to provide a comprehensive, dynamic compendium of space radiation data, enabling the scientific community to perform analyses of data from multiple detectors and to determine the radiation environment of research missions and experiments. Some of its applications include inference of absorbed radiation dose for NASA GeneLab payloads, and training predictive models as part of the 2024 FDL-X challenge. The platform is actively expanding and seeking additional data, with plans to also cover past (e.g. Shuttle, Mir) and future (e.g. Artemis) missions. The RadLab Working Group has been created to aid in this process as well as to foster collaborations among data contributors and users, to develop standards for data harmonization, and to guide the development of the platform, with the goal to establish the use of RadLab in space radiation research and to advance our understanding of the radiation environment in outer space.

Kirill Grigorev↗

Remembering Apollo 11: The 30th Anniversary Data Archive CD-ROM

On July 20, 1969, the human race accomplished its single greatest technological achievement of all time when a human first set foot on another celestial body. Six hours after landing at 4:17 p.m. Eastern Standard Time (with less than thirty seconds of fuel remaining), Neil A. Armstrong took the "small step" into our greater future when he stepped off the Lunar Module, named Eagle, onto the surface of the Moon, from which he could look up and see Earth in the heavens as no one had done before him. He was shortly joined by Edwin "Buzz" Aldrin, and the two astronauts spent twenty-one hours on the lunar surface and returned forty-six pounds of lunar rocks. After their historic walks on the Moon, they successfully docked with Michael Collins, patiently orbiting the cold but no longer lifeless Moon alone in the Command module Columbia. This CR-ROM is intended as a collection of hard to find technical data and other interesting information about the Apollo 11 mission, as well as the apollo program in general. It includes basic overviews, such as a retrospective analysis, an annotated bibliography, and history of the lunar-orbit rendezvous concept. It also contains technical data, such as mission operations reports, press kits, and news references for all of the Apollo missions, the Apollo spacecraft, and the Saturn V launch vehicle. Rounding out this CD-ROM are extensive histories of the lunar Orbiter program (the robotic predecessor to Apollo, biographies of the Apollo astronauts and other key individuals, and interesting audio-visual materials, such as video and audio clips, photo galleries, and blueprint-like diagrams of the Apollo spacecraft.

Edgar M Cortright↗

Thermal Considerations for 2039 Opposition Class Nuclear Electric Propulsion/Chemical Propulsion Crewed Mars Mission

The high specific impulse (Isp) of Nuclear Electric Propulsion (NEP) technology offers the potential for advanced space mission capabilities. However, the five critical technology elements of NEP vehicles have yet to prove technical maturity levels for consideration into mission design. In response to the critical reviews by the NASA Engineering and Safety Center (NESC) and the National Academies of Sciences, Engineering, and Medicine (NASEM), NASA’s Space Nuclear Propulsion (SNP) project created an NEP Technology Maturation Plan (TMP) for focused development of NEP technology. The TMP called for a coordinated set of technology development efforts to meet this objective. The Modular Assembled Radiators for NEP VehicLes (MARVL) Early Career Initiative (ECI) project was initiated to develop a portion of the fifth Critical Technology Element (CTE) of the NEP vehicle: the Primary Heat Rejection Subsystem (PHRS). A target application of a 2039 human-rated Mars mission was outlined in the TMP. For the outlined mission, a NEP vehicle will experience several thermal environments which will impact the design and operation of the PHRS. To maintain radiator temperatures within the required effective temperature range, the effect of natural, induced, and NEP internally generated heat loads on the radiator panel must be well understood. Furthermore, this analysis is critical for analyzing the influence of various orientations and positions of the NEP vehicle relative to nearby celestial bodies throughout the mission. This study conducted a complete enveloping analysis of the thermal environments influencing the NEP vehicle throughout the mission. Thermal analysis was conducted for the radiator panels based on the defined mission environments. This thermal analysis concludes with the selection of ideal radiator orientations for the NEP vehicle, and the identification of worst case hot and cold environmental sink temperatures throughout the mission. For the target application, the environmental sink temperature while the reactor is powered OFF or powered ON ranges from 30 K to 353 K and 2.7 K to 243 K respectively. When considering interplanetary space, the minimum environmental sink temperature when the reactor is powered OFF and the radiators are oriented “edge to Sun” is 2.7 K. The environmental thermal models generated in this study will be used for future studies with the full vehicle system model. The environmental sink temperature curves generated will be used for future radiator and component analysis to predict transient performance in the space environment. The environmental sink temperature and heat rejection capability curves will inform the trade between commissioning orbits that are in consideration. The model may also serve as a useful tool as reference for future crewed space missions, missions involving radiators or temperature sensitive equipment, or other missions requiring analysis of natural orbital thermal environments.

Nuclear Electric Propulsion↗

Autonomous Navigation Using Celestial Objects

In the twenty-first century, National Aeronautics and Space Administration (NASA) Enterprises envision frequent low-cost missions to explore the solar system, observe the universe, and study our planet. Satellite autonomy is a key technology required to reduce satellite operating costs. The Guidance, Navigation, and Control Center (GNCC) at the Goddard Space Flight Center (GSFC) currently sponsors several initiatives associated with the development of advanced spacecraft systems to provide autonomous navigation and control. Autonomous navigation has the potential both to increase spacecraft navigation system performance and to reduce total mission cost. By eliminating the need for routine ground-based orbit determination and special tracking services, autonomous navigation can streamline spacecraft ground systems. Autonomous navigation products can be included in the science telemetry and forwarded directly to the scientific investigators. In addition, autonomous navigation products are available onboard to enable other autonomous capabilities, such as attitude control, maneuver planning and orbit control, and communications signal acquisition. Autonomous navigation is required to support advanced mission concepts such as satellite formation flying. GNCC has successfully developed high-accuracy autonomous navigation systems for near-Earth spacecraft using NASA's space and ground communications systems and the Global Positioning System (GPS). Recently, GNCC has expanded its autonomous navigation initiative to include satellite orbits that are beyond the regime in which use of GPS is possible. Currently, GNCC is assessing the feasibility of using standard spacecraft attitude sensors and communication components to provide autonomous navigation for missions including: libration point, gravity assist, high-Earth, and interplanetary orbits. The concept being evaluated uses a combination of star, Sun, and Earth sensor measurements along with forward-link Doppler measurements from the command link carrier to autonomously estimate the spacecraft's orbit and reference oscillator's frequency. To support autonomous attitude determination and control and maneuver planning and control, the orbit determination accuracy should be on the order of kilometers in position and centimeters per second in velocity. A less accurate solution (one hundred kilometers in position) could be used for acquisition purposes for command and science downloads. This paper provides performance results for both libration point orbiting and high Earth orbiting satellites as a function of sensor measurement accuracy, measurement types, measurement frequency, initial state errors, and dynamic modeling errors.

Folta, David↗

Contribution of X/Ka VLBI to Multi-Wavelength Celestial Frame Studies

This paper is an update of Sotuela et al. (2011) which improves their simulated Gaia frame tie precision by approximately 10% by adding three additional VLBI observing sessions. Astrometry at X/Ka-band (8.4/32 GHz) using NASAs Deep Space Network has detected 466 quasars with accuracies of 200-300 micro-arc seconds. A program is underway to reduce errors by a factor of 2-3. From our sample, 245 sources have optical magnitudes V less than 20 and should also be detectable by Gaia. A covariance study using existing X/Ka data and simulated Gaia uncertainties for the 345 objects yields a frame tie precision of 10-15 micro-arc seconds (1 - sigma). The characterization of wavelength dependent systematic from extended source morphology and core shift should benefit greatly from adding X/Ka-band measurements to S/X-band (2.3/8.4 GHz) measurements thus helping to constrain astrophysical models of the wavelength dependence of positions.

galaxies↗

Double Asteroid Redirection Test (DART) Mission

NASA’s Double Asteroid Redirection Test (DART) mission was humanity’s first attempt to move a celestial body, demonstrating the capability to perform a kinetic impact on a planetary defense–relevant sized asteroid. DART was part of the international collaboration known as the Asteroid Impact & Deflection Assessment (AIDA), involving NASA, the European Space Agency (ESA), the Agenzia Spaziale Italiana (ASI), and scientists around the world. DART was a key step to demonstrating preparedness to respond to planetary defense scenarios, and it provides a crucial data point for likely outcomes. Near-Earth objects (NEOs) greater than 140 m in size are of particular interest to planetary defense because they have the potential to cause significant damage if they were to impact Earth, and also because they are difficult to detect, with less than 50% of the predicted population discovered as of 2022 (National Academies Press, 2022). With an appropriately sized spacecraft and enough warning (typically many years to decades), a kinetic impact can slightly alter the orbit of an asteroid in a way that, over time, prevents the asteroid from colliding with Earth in the future. DART’s target was Dimorphos, the smaller (~150-m-diameter) member of the binary asteroid system (65803) Didymos, which is a near-Earth, potentially hazardous, and well-characterized asteroid system. By simply observing changes to the system after impact and comparing them with a pre-impact reference, it was possible to use ground-based telescopes to observe the deflection in the orbit of Dimorphos after impact. Developed and operated by the Johns Hopkins University Applied Physics Laboratory (APL), the mission entered formulation in 2015 after multiple years of concept development. The project was administered according to NPR 7120.5, with technical oversight and funding through the Planetary Missions Program Office (PMPO) at Marshall Space Flight Center (MSFC) and overall support as a directed mission from NASA’s Planetary Defense Coordination Office (PDCO). The DART spacecraft hosted a singular payload, the Didymos Reconnaissance and Asteroid Camera for Optical navigation (DRACO), and a deployable CubeSat contributed by ASI named the Light Italian CubeSat for Imaging of Asteroids (LICIACube). On 11 September 2022, DART deployed LICIACube, which subsequently followed the DART spacecraft at a safe distance and observed the immediate aftermath of the DART impact. DART was designed to autonomously detect, navigate to, and impact Dimorphos. This autonomous design was chosen to maximize the probability of impact, since commanding from the ground could result in course corrections arriving too late. On the day of impact, 26 September 2022, the spacecraft’s autonomous systems successfully detected and locked on to Dimorphos, impacting its surface within 2 m of the center of the illuminated figure (Jensenius et al., 2023). No human intervention was required for a successful impact, demonstrating that humanity possesses the technology to perform a kinetic impact. Within 2 weeks of impact, it was clear that the orbit of Dimorphos had been significantly altered. On 11 October 2022, NASA Administrator Bill Nelson announced that the new orbital period of Dimorphos was shortened by approximately 32 ± 2 min, from 11 h and 55 min before impact to 11 h and 23 min after impact. With additional observations over the following months, the accuracy of this measurement improved to a –33.24 min ± 1.4 s orbital period change (Naidu et al., 2023; Scheirich et al., 2023), and Beta (β), the momentum transfer enhancement parameter, was reported to be 3.6 (Cheng et al., 2023). Subsequent studies examined the details of DART’s impact site, modeled the impact event, investigated the ejecta produced, and analyzed the dynamics of the Didymos system. These combined results clearly demonstrate that the project met all Level 1 mission requirements.

asteroid↗

Supporting Development of Satellite's Guidance Navigation and Control Software: A Product Line Approach

The NASA Goddard Space Flight Center Flight Software Branch (FSB) is developing a Guidance, Navigation, and Control (GNC) Flight Software (FSW) product line. The demand for increasingly more complex flight software in less time while maintaining the same level of quality has motivated us to look for better FSW development strategies. The GNC FSW product line has been planned to address the core GNC FSW functionality very similar on many recent low/near Earth missions in the last ten years. Unfortunately these missions have not accomplished significant drops in development cost since a systematic approach towards reuse has not been adopted. In addition, new demands are continually being placed upon the FSW which means the FSB must become more adept at providing GNC FSW functionality's core so it can accommodate additional requirements. These domain features together with engineering concepts are influencing the specification, description and evaluation of FSW product line. Domain engineering is the foundation for emerging product line software development approaches. A product line is 'A family of products designed to take advantage of their common aspects and predicted variabilities'. In our product line approach, domain engineering includes the engineering activities needed to produce reusable artifacts for a domain. Application engineering refers to developing an application in the domain starting from reusable artifacts. The focus of this paper is regarding the software process, lessons learned and on how the GNC FSW product line manages variability. Existing domain engineering approaches do not enforce any specific notation for domain analysis or commonality and variability analysis. Usually, natural language text is the preferred tool. The advantage is the flexibility and adapt ability of natural language. However, one has to be ready to accept also its well-known drawbacks, such as ambiguity, inconsistency, and contradictions. While most domain analysis approaches are functionally oriented, the idea of applying the object-oriented approach in domain analysis is not new. Some authors propose to use UML as the notation underlying domain analysis. Our work is based on the same idea of merging UML and domain analysis. Further, we propose a few extensions to UML in order to express variability, and we define precisely their semantics so that a tool can support them. The extensions are designed to be implemented on the API of a popular industrial CASE tool, with obvious advantages in cost and availability of tool support. The paper outlines the product line processes and identifies where variability must be addressed. Then it describes the product line products with respect to how they accommodate variability. The Celestial Body subdomain is used as a working example. Our results to date are summarized and plans for the future are described.

McComas, David↗

Tidal Heating in Multilayered Terrestrial Exoplanets

The internal pattern and overall magnitude of tidal heating for spin-synchronous terrestrial exoplanets from 1 to 2.5 R(sub E) is investigated using a propagator matrix method for a variety of layer structures. Particular attention is paid to ice-silicate hybrid super-Earths, where a significant ice mantle is modeled to rest atop an iron-silicate core, and may or may not contain a liquid water ocean. We find multilayer modeling often increases tidal dissipation relative to a homogeneous model, across multiple orbital periods, due to the ability to include smaller volume low viscosity regions, and the added flexure allowed by liquid layers. Gradations in parameters with depth are explored, such as allowed by the Preliminary Earth Reference Model. For ice-silicate hybrid worlds, dramatically greater dissipation is possible beyond the case of a silicate mantle only, allowing non-negligible tidal activity to extend to greater orbital periods than previously predicted. Surface patterns of tidal heating are found to potentially be useful for distinguishing internal structure. The influence of ice mantle depth and water ocean size and position are shown for a range of forcing frequencies. Rates of orbital circularization are found to be 10-100 times faster than standard predictions for Earth-analog planets when interiors are moderately warmer than the modern Earth, as well as for a diverse range of ice-silicate hybrid super-Earths. Circularization rates are shown to be significantly longer for planets with layers equivalent to an ocean-free modern Earth, as well as for planets with high fractions of either ice or silicate melting.

celestial mechanics↗

Autonomous Navigation of a Lunar Relay Using GNSS and Other Measurements

Many of the highest priority destinations at the Moon lack a continuous view of Earth, such as the lunar poles or lunar far side. Exploration of these sites will require spacecraft in cislunar space to relay communications and provide position, navigation, and timing (PNT) services. Accurate knowledge of relay position, velocity, and time is essential to these services. This paper describes a concept for a PNT Instrument being developed for the Lunar Communications Relay and Navigation Systems (LCRNS) Project. The instrument is intended as a payload that would enable autonomous, on-board, real-time navigation and timing using Global Navigation Satellite System (GNSS), optical navigation, and one-way measurements from Earth-based ground stations. Hardware-in-the-loop simulations using flight software are used to realistically characterize performance on hardware platforms with a path to flight. These results provide preliminary validation of the proposed PNT Instrument, demonstrate the benefits of augmenting GNSS with other measurements, and serve as an insightful reference for the design of future lunar missions, including those that will operate within the LunaNet framework of standards. This instrument concept relies on several technologies developed at NASA Goddard Space Flight Center (GSFC). For GNSS observables, the instrument relies on the high-altitude NavCube 3 mini (NC3m) GNSS receiver specifically designed for cislunar applications. The autoNGC system, which consists of flight software and a hardware platform, is responsible for fusing the observables using its extended Kalman filter, the Goddard Enhanced Onboard Navigation System (GEONS). Optical navigation observables are processed within autoNGC (“autonomous Navigation, Guidance, and Control”) using the Goddard Image Analysis & Navigation Tool (GIANT) which is also responsible for simulating high-fidelity images for test and analysis. In addition to describing the PNT Instrument and its components, the paper will present predicted performance based on simulation results. As a baseline, it will present GNSS-only hardware-in-the loop results using a NC3m test unit to process Spirent-simulated GPS signals in a potential lunar relay trajectory: a 12-hour elliptical frozen lunar orbit (ELFO). GEONS then processes the GPS pseudorange and time differenced carrier phase measurements to estimate and propagate the relay state (position, velocity, and time). These results extend previously published work that showed preliminary ELFO performance. Previous work has shown the importance of other measurement types, so additional simulations are performed which augment GNSS with ground station observables and several methods of optical navigation, including celestial navigation, limb-finding (e.g., observations of the lunar horizon), and terrain relative navigation (TRN). TRN involves correlating simulated predicted images of the lunar surface with actual imagery; misalignments of landmarks identified in each image are translated into relay state updates. TRN is valuable as a measurement of the relay’s state relative to the Moon, especially during GNSS outages or after maneuvers. One-way Pseudorange and Doppler measurements from Earth-based ground stations are also simulated. The full set of observables is processed using autoNGC. These simulations make use of autoNGC and NC3m test units, a lab atomic clock, and a pulse-per-second (PPS) generation and distribution system. This combination of subsystems, and the hardware platforms used in this analysis, represents a PNT Instrument that could be flown on a lunar relay. Results from the hardware-in-the-loop simulations presented in this paper provide a preliminary assessment of the achievable navigation performance of this instrument concept. PNT Instrument performance is compared to the GPS-only performance, and a discussion is provided on the apparent merits and challenges of each measurement type.

Ben Ashman↗

Celestial Mapping System and Digital Lunar Library Initiative

We are preparing to create an interactive, global 3D lunar environment with integrated dataset and AI/ML tools to provide unique value to mission planners, scientists and the entire lunar community. This lunar environment will be based on NASA Ames Celestial Mapping System (CMS) [1] and Digital Lunar Library (DLL) Initiative. CMS provides a 3D virtual Lunar Globe with extensive user friendly tool sets, that include high resolution terrain visualization, elevation profiles, measurement kits, slope analysis, path optimization, line of sight analysis, equipment planning and placement tools and many other functionalities [1]. It has a thick client with less overhead to access hardware resources. This allows features such as terrain profiling and distance calculations to be performed on the client and on the fly. The application is developed to provide situational and domain awareness on the Lunar surface, planning capabilities for equipment placements and traverse path optimization. As data becomes available, CMS has the capabilities to integrate data sets that change dynamically in real-time, which will be useful for monitoring satellites and remotely-sensed data on the Lunar surface. CMS supports importing synthetic features in a variety of 3D, 2D, vector and raster formats. In the future, these capabilities will be enhanced by incorporating AI/ML tools and a plug-in architecture to enable customization by the user groups. With the help of DLL we will be able to : 1) Amplify the value of lunar information with AI-powered data enhancements 2) Acquire and integrate lunar data with AI-assisted georectification and homogenization 3) Analyze lunar data with advanced 3D visualization, intelligent search-by-example 4) Apply lunar data insights to specific use cases with an open plug-in architecture. The CMS-DLL initiative will have several potential use cases for NASA and the lunar community in general, including subsurface lava tube visualization and analysis, soil analysis, in-situ lunar resource visualization and representation on 3D globe, and data analytics for utilization. REFERENCES: [1] https://celestial.arc.nasa.gov/

3D Globe↗

Global 3D Data Visualization and Analysis Platform with Advanced Machine Learning Capabilities in Support of Lunar Exploration

Introduction: The science goals for NASA’s Artemis program include: a) Understanding the character and origin of lunar polar volatiles, b) Conducting experimental science in the lunar environment and c) Investigating and mitigating exploration risks. The permanently shadowed regions (PSRs) on the Lunar south pole are expected to host large quantities of water-ice and volatiles that are important for sustainable Lunar exploration. There are several missions such as onboard Korea Pathfinder Lunar Orbiter (KPLO: Korean name Danuri) with onboard ShadowCam camera, Astrobotic Peregrine Mission One [4], and other efforts underway to obtain high resolution topographic, minerals, volatiles and other information on the moon. We envision a need in immediate future for platforms to integrate these data sets, provide rendering and visualization capabilities in the context of a 3D Lunar globe for easier information access and analysis. NASA's Celestial Mapping System (CMS) is developed to address the need for 3D tools for planetary science investigations, mission planning, in-situ operations, in a 3D-first design constructed around a unified view of a planetary globe. At present CMS provides many critical functionalities that include: 1) equipment planning and optimized placement on Lunar surface 2) line-of-sight (LOS) analysis 3) powerful measurement tools based on 3D terrain with realistic 3D models to represent rovers, astronauts and equipment 4) visualization of derived mapping products (e.g. resource maps), and 5) a data engine for hosting new observations that are not available in other contemporary lunar data tools. Planetary Data Ingestion: CMS can consume and analyze data from locally hosted and external third party sources. It is compatible with Open Geospatial Consortium (OGC) data and file standards and currently integrates datasets from the Astrogeology Science Center of USGS. This includes global and local data acquired from NASA (LRO, Clementine, Lunar Orbiter) and JAXA (SELENE/Kaguya), with capability of integrating more datasets. In addition, users can specify other WMS-hosted data endpoints, which CMS can then query and stream data from automatically. To set-up an automated process for ingestion and accurate rendering, visualization and analysis of external 3rd party planetary datasets within CMS, we initiated the process of ingesting unique dataset of super-enhanced images of the permanently shadowed regions (PSRs) at the lunar poles which were produced by the Hyper-effective nOise Removal U-net Software (HORUS) tool. This tool was developed to enhance the extremely low-light images of the interior of PSRs and provide the ability to see within these regions at and discern surface features (i.e. boulders and craters) down to 3 meters in size. We focused on the Nobile region on the Lunar south pole, selected site for VIPER mission and stitched several images to create a high-resolution map within one of the PSR of Nobile crater. Figure 1 shows the dark PSR zone form the original NAC layer of LRO as the base layer (left image) and the illuminated areas within that crater (center) which was created by ingesting and merging several of HORUS generated images. At present we employ a semi-automated process to ensure spatial accuracy and merger of several overlapping zones. However, we are in the process of completely automating this process by employing AI based techniques that would rank, sort, and stack the images based on their information density. The georectification of the images would employ selected features. Analysis on Ingested Planetary Datasets: Once an external planetary data-set is successfully ingested, georectified and merged seamlessly as a data-layer; CMS’ numerous analysis tools can be used on this data. A Line of Sight (LOS) tool has been developed for CMS which analyzes terrain profiles and obstructions to determine visibility for remote observers. Figure 1 (right image) shows the viewshed analysis on the same PSR in the Nobile region. The yellow pin shows the observer location outside the PSR. The yellow area shows the visible part of PSR. The obstructed area with no visibility for the observer is shown in red. The Measurements tool allows the user to take area and distance measurements of features on the terrain using various shapes. Measurement type can be specified in a number of ways: Line, Path, Polygon, Circle, Ellipse, Square, Rectangle or Freehand. Once the shape is specified, elevation information can then be extracted along each of these shapes. Figure 2 (left) shows the measurements performed on a crater n illuminated PSR in Nobile region. The equipment placement tool allows the user to place a 3D equipment model at a desired location and analyze its coverage area. The equipment placement tool is coupled with LOS to determine the coverage. Figure 2 (right) shows an equipment placed on the Lunar terrain and it’s coverage area. The red rays are blocked sight lines and the green rays are non-obstructed sight lines with the cyan lines showing the point of intersection with the terrain. More details are provided in the video demonstrations in Reference 5. Overcoming Polar Distortions: 3D geospatial applications exhibit significant distortions in polar imagery due to several reasons: 1) distortions in the source imagery, 2) incompatible tessellation algorithms at the poles, and 3) map projections. We are leveraging new tessellation algorithms and reprojecting data using projections that are better suited for Lunar poles. The goal is to seamlessly switch to polar projections while maintaining 3D view and navigation.

Maps↗

Global 3D Data Visualization and Analysis Platform With Advanced Machine Learning Capabilities in Support of Lunar Exploration

Introduction: The science goals for NASA’s Artemis program include: a) Understanding the character and origin of lunar polar volatiles, b) Conducting experimental science in the lunar environment and c) Investigating and mitigating exploration risks [1]. The permanently shadowed regions (PSRs) on the Lunar south pole are expected to host large quantities of water-ice and volatiles that are important for sustainable Lunar exploration [2]. There are several missions such as onboard Korea Pathfinder Lunar Orbiter (KPLO: Korean name Danuri) with onboard ShadowCam camera [3], Astrobotic Peregrine Mission One [4], and other efforts underway to obtain high resolution topographic, minerals, volatiles and other information on the moon. We envision a need in immediate future for platforms to integrate these data sets, provide rendering and visualization capabilities in the context of a 3D Lunar globe for easier information access and analysis. NASA's Celestial Mapping System (CMS) [5] is developed to address the need for 3D tools for planetary science investigations, mission planning, in-situ operations, in a 3D-first design constructed around a unified view of a planetary globe. At present CMS provides many critical functionalities that include: 1) equipment planning and optimized placement on Lunar surface 2) line-of-sight (LOS) analysis 3) powerful measurement tools based on 3D terrain with realistic 3D models to represent rovers, astronauts and equipment 4) visualization of derived mapping products (e.g. resource maps), and 5) a data engine for hosting new observations that are not available in other contemporary lunar data tools [5, 7]. Planetary Data Ingestion: CMS can consume and analyze data from locally hosted and external third party sources. It is compatible with Open Geospatial Consortium (OGC) data and file standards and currently integrates datasets from the Astrogeology Science Center of USGS. This includes global and local data acquired from NASA (LRO, Clementine, Lunar Orbiter) and JAXA (SELENE/Kaguya), with capability of integrating more datasets. In addition, users can specify other WMS-hosted data endpoints, which CMS can then query and stream data from automatically. To set-up an automated process for ingestion and accurate rendering, visualization and analysis of external 3rd party planetary datasets within CMS, we initiated the process of ingesting unique dataset of super-enhanced images of the permanently shadowed regions (PSRs) at the lunar poles which were produced by the Hyper-effective nOise Removal U-net Software (HORUS) tool [8]. This tool was developed to enhance the extremely low-light images of the interior of PSRs and provide the ability to see within these regions at and discern surface features (i.e. boulders and craters) down to 3 meters in size. We focused on the Nobile region on the Lunar south pole, selected site for VIPER mission and stitched several images to create a high-resolution map within one of the PSR of Nobile crater. Figure 1 shows the dark PSR zone form the original NAC layer of LRO as the base layer (left image) and the illuminated areas within that crater (center) which was created by ingesting and merging several of HORUS generated images. At present we employ a semi-automated process to ensure spatial accuracy and merger of several overlapping zones. However, we are in the process of completely automating this process by employing AI based techniques that would rank, sort, and stack the images based on their information density. The georectification of the images would employ selected features. Analysis on Ingested Planetary Datasets: Once an external planetary data-set is successfully ingested, georectified and merged seamlessly as a data-layer; CMS’ numerous analysis tools can be used on this data. A Line of Sight (LOS) tool has been developed for CMS which analyzes terrain profiles and obstructions to determine visibility for remote observers [5,6]. Figure 1 (right image) shows the viewshed analysis on the same PSR in the Nobile region. The yellow pin shows the observer location outside the PSR. The yellow area shows the visible part of PSR. The obstructed area with no visibility for the observer is shown in red. The Measurements tool allows the user to take area and distance measurements of features on the terrain using various shapes. Measurement type can be specified in a number of ways: Line, Path, Polygon, Circle, Ellipse, Square, Rectangle or Freehand. Once the shape is specified, elevation information can then be extracted along each of these shapes. Figure 2 (left) shows the measurements performed on a crater n illuminated PSR in Nobile region. The equipment placement tool allows the user to place a 3D equipment model at a desired location and analyze its coverage area. The equipment placement tool is coupled with LOS to determine the coverage. Figure 2 (right) shows an equipment placed on the Lunar terrain and it’s coverage area. The red rays are blocked sight lines and the green rays are non-obstructed sight lines with the cyan lines showing the point of intersection with the terrain. More details are provided in the video demonstrations in Reference 5. Overcoming Polar Distortions: 3D geospatial applications exhibit significant distortions in polar imagery due to several reasons: 1) distortions in the source imagery, 2) incompatible tessellation algorithms at the poles, and 3) map projections. We are leveraging new tessellation algorithms and reprojecting data using projections that are better suited for Lunar poles. The goal is to seamlessly switch to polar projections while maintaining 3D view and navigation.

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