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This slide presentation discusses how in the early concept studies the communications architecture plays an important part: The communications architecture is the arrangement, or configuration of satellites and ground systems in a space system, and the network of communications links that transfers information between them.
Understanding the physical and chemical processes which led to the formation of the terrestrial planets remains one of the principal challenges of the Earth and planetary science communities. However, direct traces of the earliest stages of planet building have generally been wiped out on larger bodies such as the Earth or Mars, obscuring our view of how that process occurred. On the other hand, the planet building process would appear to have been arrested prematurely in the region between Mars and Jupiter, now populated by several hundred thousand compositionally diverse objects that escaped accretion into larger planets. Of these, the asteroid 4 Vesta is of particular interest as it is large (520 km diameter), and known to have a basaltic surface dominated by pyroxenes [1, 2]. Furthermore, visible-IR spectra of Vesta obtained by ground and space-based telescopes are remarkably similar to laboratory spectra measured on meteorites of the Howardite-Eucrite-Diogenite clan (HED), leading to the paradigm that the HEDs came from Vesta [2]. Geochemical and petrological studies of the HEDs confirm the differentiated nature of the near-surface region of their parent body, and imply that crust extraction occurred well within the first 10Ma of solar system history [3]. Vesta is therefore a prime target for studies that aim to constrain the earliest stages of planet building, and for that reason it is currently the subject of the Dawn mission [4].
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The Consultative Committee for Space Data Systems (CCSDS) has been developing data and communications standards since 1982, with the objective of providing interoperability for enabling international collaboration for spaceflight missions. As data and communications technology has advanced, CCSDS has progressed to capitalize on existing products when available and suitable for spaceflight, and to develop innovative new approaches when available products fail. The current scope of the CCSDS architecture spans the end-to-end data architecture of a spaceflight mission, with ongoing efforts to develop and standardize cutting-edge technology. This manuscript describes the overall architecture, the position of CCSDS in the standards and international mission community, and some CCSDS processes. It then highlights in detail several of the most interesting and critical technical areas in work right now, and how they support collaborative missions. Special topics include: Delay/Disruption Tolerant Networking (DTN), Asynchronous Message Service (AMS), Multispectral/Hyperspectral Data Compression (MHDC), Coding and Synchronization, Onboard Wireless, Spacecraft Monitor and Control, Navigation, Security, and Time Synchronization/Correlation. Broad international participation in development of CCSDS standards is encouraged.
Concepts and prototypes1,2 are discussed for a data-based console logger (D-Logger) to meet new challenges for coordination among flight controllers arising from new exploration mission concepts. The challenges include communication delays, increased crew autonomy, multiple concurrent missions, reduced-size flight support teams that include multidisciplinary flight controllers during quiescent periods, and migrating some flight support activities to flight controller offices. A spiral development approach has been adopted, making simple, but useful functions available early and adding more extensive support later. Evaluations have guided the development of the D-Logger from the beginning and continue to provide valuable user influence about upcoming requirements. D-Logger is part of a suite of tools designed to support future operations personnel and crew. While these tools can be used independently, when used together, they provide yet another level of support by interacting with one another. Recommendations are offered for the development of similar projects.
NASA Goddard Earth Sciences Data and Information Services Center (GESDISC) is one of the 12 NASA Science Mission Directorate Data Centers. The main goal of GESDISC is to provide earth science data, information, and services to the earth science data community. Consequently, data discovery is at the center of our mission and our search engine is the primary tool for our users to interact, find, and access our data. Existing search approaches are largely focused on hard-matching of keywords in the search query with dataset metadata. Here we propose to expand the search by introducing a complementary natural language processing (NLP) search. At the heart of our proposed NLP search, we trained a joint embedding using scientific text corpus and a curated set of dataset metadata. The embedding learns the association between words in our dataset metadata and those of the scientific text corpus. This enables us to go beyond simple hard-matching of a query and data set metadata and have a notion of “similarity” between the search query and the datasets. We further integrated our NLP search into the Elastic Search (ES) framework leveraging similarity search capabilities offered through the “dense_vector” field type. Our preliminary evaluations show that our proposed NLP search has the potential to be utilized to complement the existing search engine and serve as a base for a dataset recommendation system.
Attention is given to the deliberations of NASA's Earth Observing System (EOS) Science and Mission Requirements Working Group, which has addressed the requirements and prospects for low earth orbit sensor platforms in the 1990s. The proposed EOS network would link data users with mission data repositories. Three EOS instrument packages have been chosen on the basis of synergistic instrument groupings for making simultaneous observations of selected phenomena over a variety of wavelengths.
A global cloud cover data set, derived from the USAF 3D NEPH Analysis, was developed for use in climate studies and for Earth viewing applications. This data set contains a single parameter - total sky cover - separated in time by 3 or 6 hr intervals and in space by approximately 50 n.mi. Cloud cover amount is recorded for each grid point (of a square grid) by a single alphanumeric character representing each 5 percent increment of sky cover. The data are arranged in both quarterly and monthly formats. The data base currently provides daily, 3-hr observed total sky cover for the Northern Hemisphere from 1972 through 1977 less 1976. For the Southern Hemisphere, there are data at 6-hr intervals for 1976 through 1978 and at 3-hr intervals for 1979 and 1980. More years of data are being added. To validate the data base, the percent frequency of or = 0.3 and or = 0.8 cloud cover was compared with ground observed cloud amounts at several locations with generally good agreement. Mean or other desired cloud amounts can be calculated for any time period and any size area from a single grid point to a hemisphere. The data base is especially useful in evaluating the consequence of cloud cover on Earth viewing space missions. The temporal and spatial frequency of the data allow simulations that closely approximate any projected viewing mission. No adjustments are required to account for cloud continuity.
This paper presents the results of the HELIOS (Hardened Extremely Long Life In-formation Optical Storage) mission on the International Space Station (ISS) which tested a unique solution for the long-term storage and retrieval of data in space. For this mission Creative Technology (CTech) developed test media—termed WORF (Write Once, Read Forever)—to validate whether this patented technology will survive all critical parameters for harsh space-based environments including microgravity and ionizing radiation. The HELIOS experiment confirmed that the WORF media is impervious to ionizing radiation, microgravity, solar (plasma) eruptions, and the stress from 8 Gs of the launch including extreme temperature expo-sure. The principal results indicate that there has been no discernible degradation of the media after 8 months on the ISS as compared to a control set of media stored on the ground. This data validated the media’s survivability for harsh space environments for long-term and deep space missions. In addition to the space environment, we are confident that WORF technology can be used for data storage where space-related and other long-term or archival integrity is critical such as: geospatial collections from satellites; space weather archives; past, ongoing, and future space mission media and documentation files; the deep space Gate-way program; as well as Big Data applications such as the Vera C. Rubin astronomical observatory (formerly the LSST). WORF technology for the HELIOS experiment uses a proven archival media, redesigned, re-purposed and patented by CTech to store digital data for long periods, measured in decades and possibly centuries. The media stores standing waves embedded in a substrate that capture the precise col-ors or wavelengths projected onto the media. The colors represent numerical data, with each data location storing multiple superimposed wavelengths, which facilitate the storage of multiple data bytes (rather than just zeros and ones); advanced mathematical permutations allow for extremely large data density equal to or greater than contemporary data storage de-vices. These colors cannot fade or degrade over time since the standing waves are physically stabilized (fully oxidized) metallic silver; no dyes are embedded for this storage system, and silver ions resist micro-bacterial and fungal contamination
Analysis of flight data from previous missions indicates that anomalous Sun sensor readings could be caused by Earth albedo interference. A previous Sun sensor study presented a detailed mathematical model of this effect. The model can be used to study the effect of both diffusive and specular reflections and to improve Sun angle determination based on perturbed Sun sensor measurements, satellite position, and an approximate knowledge of attitude. The model predicts that diffuse reflected light can cause errors of up to 10 degrees in Coarse Sun Sensor (CSS) measurements and 5 to 10 arc sec in Fine Sun Sensor (FSS) measurements, depending on spacecraft orbit and attitude. The accuracy of these sensors is affected as long as part of the illuminated Earth surface is present in the sensor field of view. Digital Sun Sensors (DSS) respond in a different manner to the Earth albedo interference. Most of the time DSS measurements are not affected, but for brief periods of time the Earth albedo can cause errors which are a multiple of the sensor least significant bit and may exceed one degree. This paper compares model predictions with Tropical Rainfall Measuring Mission (TRMM) CSS measurements in order to validate and refine the model. Methods of reducing and mitigating the impact of Earth albedo are discussed. ne CSS sensor errors are roughly proportional to the Earth albedo coefficient. Photocells that are sensitive only to ultraviolet emissions would reduce the effective Earth albedo by up to a thousand times, virtually eliminating all errors caused by Earth albedo interference.
Landsat 9* (L9) is the successor mission to Landsat 8 (L8) previously known as Landsat Data Continuity Mission (LDCM). Both missions are large unmanned remote sensing satellites operating in sunsynchronous polar orbits. As opposed to L8/LDCM, systems engineers for L9 incorporated Micrometeoroid/Orbital Debris (MMOD) protection for small object collisions as part of the L9’s mission success criteria. In other words, the NASA Process for Limiting Orbital Debris (NASA-STD-8719.14A) only calls for analyses of the protection of disposal-critical hardware, but L9 opted to also assess and provide small particle penetration protections for all observatory components including instruments that are not part of the spacecraft components needed for controlled reentry. Systems engineers at Goddard developed a design process to protect against MMOD during the life of Low Earth Orbit (LEO) observatories, and in particular the Landsat 9 Mission. Simply stated, this design process enhanced the effectiveness of existing Multi-Layer Insulation (MLI) to provide the needed protection. The end goal of the design process was to establish a necessary blanket areal density for a given electronics box or instrument wall thickness and a separation between the outer MLI blanket and the structure underneath. The trade space was presented as a set of design curves for different combinations of blanket density, box wall thickness, and separation distance between MLI and structure. An advantage of this process was that it is largely independent of MMOD flux data on a surface-by surface basis. Ultimately, cost savings should result from incorporating small object penetration protection early in the design cycle, rather than adding spot shielding blankets later as needed to meet an overall penetration risk standard (the more traditional approach). The approach and implementation to the L9 Observatory design will be addressed in this paper. *L9 is a joint mission being formulated, implemented, and operated by the National Aeronautics and Space Administration (NASA) and the Department of the Interior’s (DOI) United States Geological Survey (USGS).
High-quality, well-governed data is essential for accelerating discovery and achieving operational excellence across DOE and national laboratory missions. The Livewire Data Platform is a DOE-supported platform that offers automated assessments of data quality, standardization, provenance, and Artificial Intelligence (AI) readiness. It allows researchers and data practitioners to systematically and easily evaluate datasets against established governance criteria and prepare them for advanced analytics. Livewire addresses critical challenges in DOE's data ecosystem with integrated capabilities for metadata validation, provenance tracking, and schema alignment. This platform's automated workflows assist users in identifying data quality gaps, enhancing interoperability between datasets collected from various stakeholders, and ensuring compliance with DOE data standards, all while reducing manual curation efforts. Additionally, we will discuss its AI readiness framework, which is being developed to prepare datasets for training models, developing advanced analytic tools, and machine learning applications. Using some of the more than one hundred tabular datasets on Livewire, processed with this open-source methodology, we will demonstrate how Livewire can serve as a model for scalable, standards-driven data management. This approach provides a pathway to leverage existing and future datasets within the DOE, boosting innovation and efficiency across national laboratories.