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NASA NTRSDate not supplied

Hybrid Flush and Synthetic Air Data Filter for Entry Vehicle Atmospheric State Estimation

A hybrid flush/synthetic air data sensing filter utilizing Kalman-Schmidt and Rach-Tung-Striebel smoothers is developed to obtain entry vehicle atmosphere estimates. The filter/smoother blends information from pressure sensors distributed on the heatshield with measurements of the vehicle aerodynamic forces and moments computed from mass properties and inertial measurement unit data, and prior estimates of the atmosphere. The filter produces estimates of the atmospheric conditions along the entry trajectory, and systematic error estimates to reconcile differences between the pressure and aerodynamic data sources. The filter is applied to data acquired during the Mars Science Laboratory and Mars 2020 entry, descent, and landing at Gale crater and at Jezero crater, respectively. The results show that the hybrid filter produces estimates of the freestream flight condition with lower uncertainty than either the flush or synthetic air data algorithms. The filter accomplishes this result by incorporating additional data and computing estimates of systematic error parameters in the pressure data and the aerodynamic model to further reduce the uncertainties.

Christopher D. Karlgaard↗
NASA NTRSDate not supplied

James Webb Space Telescope Navigation Optimization Challenges

The James Webb Space Telescope (JWST) is a NASA flagship mission launched on December 25, 2021. The early orbit phase was highlighted by three midcourse correction burns that were performed to maneuver the vehicle into a libration orbit at the second Sun-Earth-Moon (SEM) libration point (L2). During the coast to L2, the vehicle’s primary observatory and sunshield were deployed. Once the tennis-court-sized sunshield was unfurled and tensioned into place, the large area exposed to solar radiation pressure (SRP) dictated that the SRP force model would need to account for the vehicle’s geometry, reflective properties, and orientation relative to the Sun. Following the insertion of JWST into its L2 libration orbit on January 24, 2022, the commissioning phase for the vehicle’s observatory commenced along with the first cycle of routine station-keeping maneuvers. The NASA Goddard Space Flight Center’s Flight Dynamics Facility (FDF) provides navigation services for the JWST mission. The FDF serves as the prime or backup navigation operations center for more than 30 active missions spanning a wide array of flight regimes performing orbit determination, maneuver planning, trajectory optimization, and tracking data evaluation. Definitive orbit determination for JWST is performed by the FDF using an Extended Kalman Filter (EKF) to estimate the vehicle’s trajectory and reflective properties using Deep Space Network (DSN) TRK-2-34 tracking data and spacecraft attitude telemetry. For the purposes of orbit prediction and station-keeping maneuver targeting, the sensitivity of the SRP force to the vehicle’s orientation requires that predictive attitude information must be incorporated to generate accurate orbit predictions and maneuver plans. Predictive attitude plans are provided to the FDF by the JWST Spacecraft Operations Center (SOC). Short-term (28 day) orbit predictions are propagated using a Short Range Attitude Plan (SRAP) to model the vehicle’s future attitude states for up to a week. SRAP attitude data is highly reliable, as it reflects finalized planned attitude states that the vehicle will be commanded to attain during the ensuing week. A Long Range Attitude Plan (LRAP) can be implemented to model predicted attitude states beyond one week, but these predictions are tentative and subject to revision due to changes in science operations plans. Instead, a conservative approach of applying a Sun-Pointing Neutral (SPN) attitude configuration is utilized for long-term (2 year) orbit predictions where reliable planned attitude data is not available. SPN attitude mode aligns the net SRP force along the JWST-to-Sun vector where it becomes independent of the vehicle’s angle of rotation about this vector, defined as the Sun yaw. Given the dynamic instability of the libration orbit, station-keeping thrust must be applied in either the sunward or anti-sunward direction to balance the resulting orbit. The attitude constraints of the vehicle also impose limits on the available pointing directions for station-keeping thrusters. The thrusters cannot be aligned with the optimal pointing direction for sunward maneuvers, rendering sunward maneuvers to be significantly less fuel efficient than anti-sunward maneuvers. Consequently, station-keeping maneuvers must be targeted to balance the orbit while ensuring that the next maneuver will also be performed in the anti-sunward direction to optimize propellant usage. When targeting a station-keeping maneuver, the attitude and SRP modeling configuration which is applied to the predicted post-maneuver trajectory will dictate the direction of the subsequent station-keeping maneuver, assuming nominal propulsion system performance. If the predicted post-maneuver attitude states result in an SRP model which under-predicts the cumulative SRP impact on the post-maneuver orbit, a targeted anti-sunward maneuver will be larger than necessary and the next maneuver will need to be executed sunward in order to compensate. In contrast, an anti-sunward maneuver which is targeted using an SRP model which over-predicts the cumulative SRP impact will achieve station-keeping while ensuring that the next maneuver will likewise be performed anti-sunward. For this reason, station-keeping maneuvers are targeted while applying the SPN attitude mode, as this mode entails the largest possible SRP area cross-section and therefore a larger modeled cumulative SRP impact. This paper documents the NASA Goddard Space Flight Center’s FDF support for JWST on-orbit operations and the analysis projects undertaken utilizing the experiences and data accumulated throughout the first full year of routine science operations. The results of these analysis efforts have been used to implement improvements to orbit prediction accuracy and maneuver efficiency which have the potential to prolong the lifespan of JWST to continue to conduct ground-breaking infrared astronomy for decades to come.

Flight Dynamics↗
NASA NTRS2003

Software Reliability 2002

In FY01 we learned that hardware reliability models need substantial changes to account for differences in software, thus making software reliability measurements more effective, accurate, and easier to apply. These reliability models are generally based on familiar distributions or parametric methods. An obvious question is 'What new statistical and probability models can be developed using non-parametric and distribution-free methods instead of the traditional parametric method?" Two approaches to software reliability engineering appear somewhat promising. The first study, begin in FY01, is based in hardware reliability, a very well established science that has many aspects that can be applied to software. This research effort has investigated mathematical aspects of hardware reliability and has identified those applicable to software. Currently the research effort is applying and testing these approaches to software reliability measurement, These parametric models require much project data that may be difficult to apply and interpret. Projects at GSFC are often complex in both technology and schedules. Assessing and estimating reliability of the final system is extremely difficult when various subsystems are tested and completed long before others. Parametric and distribution free techniques may offer a new and accurate way of modeling failure time and other project data to provide earlier and more accurate estimates of system reliability.

Wallace, Dolores R.↗
NASA NTRS2018

Quantum Machine Learning

Quantum computing promises an unprecedented ability to solve intractable problems by harnessing quantum mechanical effects such as tunneling, superposition, and entanglement. The Quantum Artificial Intelligence Laboratory (QuAIL) at NASA Ames Research Center is the space agency's primary facility for conducting research and development in quantum information sciences. QuAIL conducts fundamental research in quantum physics but also explores how best to exploit and apply this disruptive technology to enable NASA missions in aeronautics, Earth and space sciences, and space exploration. At the same time, machine learning has become a major focus in computer science and captured the imagination of the public as a panacea to myriad big data problems. In this talk, we will discuss how classical machine learning can take advantage of quantum computing to significantly improve its effectiveness. Although we illustrate this concept on a quantum annealer, other quantum platforms could be used as well. If explored fully and implemented efficiently, quantum machine learning could greatly accelerate a wide range of tasks leading to new technologies and discoveries that will significantly change the way we solve real-world problems.

Biswas, Rupak↗
NASA NTRS2012

Improved Maneuver Reconstructions for the GRAIL Orbiters

Maneuver reconstructions for the Gravity Recovery and Interior Laboratory (GRAIL) A and B lunar orbiters were improved through updates to the orbit determination filter and dynamic models. Consistent reconstructions of the 27 GRAIL A and B maneuvers from the Trans-Lunar Cruise phase in the fall of 2011 through the Transition to Science Formation phase in February 2012 were performed. Standard methods of orbit determination were applied incorporating the latest dynamic models and filter strategies developed by the GRAIL Navigation and Science Teams, including a high resolution, 420 x 420 degree and order lunar spherical harmonic gravity field model. For Trans-Lunar Cruise for GRAIL-A (TLC-A), all maneuvers executed with delta V errors below 5.50 +/- 0.50 mm/s and pointing errors below 0.25 degrees. GRAIL-A lunar orbit maneuvers had delta V errors below 30.0 mm/s and pointing errors below 0.51 degrees. For TLC-B, all maneuvers executed with delta V errors below 8.60 +/- 1.41 mm/s and pointing errors below 0.300 degrees. GRAIL-B maneuvers in lunar orbit executed with maximum delta V errors of 25.0 mm/s and pointing error of 0.43 degrees. These maneuver reconstructions will enable the GRAIL Navigation Team to better characterize the main engine performance of each spacecraft. This will help the Navigation Team to navigate low (greater than 8 km) altitude orbits during the extended mission phase in the fall of 2012.

lunar mapping↗
NASA NTRS1990

The ISES: A non-intrusive medium for in-space experiments in on-board information extraction

The Information Science Experiment System (ISES) represents a new approach in applying advanced systems technology and techniques to on-board information extraction in the space environment. Basically, what is proposed is a 'black box' attached to the spacecraft data bus or local area network. To the spacecraft the 'black box' appears to be just another payload requiring power, heat rejection, interfaces, adding weight, and requiring time on the data management and communication system. In reality, the 'black box' is a programmable computational resource which eavesdrops on the data network, taking and producing selectable, real-time science data back on the network. This paper will present a brief overview of the ISES Concept and will discuss issues related to applying the ISES to the polar platform and Space Station Freedom. Critical to the operation of ISES is the viability of a payload-like interface to the spacecraft data bus or local area network. Study results that address this question will be reviewed vis-a-vis the solar platform and the core space station. Also, initial results of processing science and other requirements for onboard, real-time information extraction will be presented with particular emphasis on the polar platform. Opportunities for a broader range of applications on the core space station will also be discussed.

Murray, Nicholas D.↗
NASA NTRS2008

Twentieth Century Moon: The Evolution of Lunar Science, 1955 - 2002

Here we discuss thc bibliographic record of Lunar Science as published in refereed journals from 1955 to 2002. New tools in bibliometrics, i.e. the study of publications and citations, reveal the structure of this scientific field by measuring and visualizing connections between published papers. This approach is especially powerful when applied to a well defined field such as Lunar Science, which is strongly affected by policy and the actions resulting from policy, most obviously gathering samples from the Moon. This poster presents some results obtained by processing a dataset of lunar science bibliographic records through a bibliographic visualization program.

Templeton, T. C.↗
NASA NTRS2019

Deep Mapping of Small Solar System Bodies with Galactic Cosmic Ray Secondary Particle Showers

We will investigate the use of galactic cosmic ray (GCR) secondary particles to probe the deep interiors of small solar system bodies (SSBs), including comets, asteroids, and geologic structures on the surfaces of airless bodies. Applications include solar system science, planetary defense, and resource utilization. Our Phase I study demonstrated that muons, the long-range charged component of GCR showers, can penetrate SSBs up to a km in diameter, providing information on their interior structure. Muons produced in Earth’s atmosphere have been applied to image the interior of large objects for science and engineering. In Phase I, we found that the production of muons in the solid surfaces of airless bodies is much smaller than in Earth’s atmosphere. Nevertheless, the flux of transmitted muons is sufficient to detect inclusions within an asteroid or comet in a reasonable amount of time, ranging from hours to weeks, depending on the size of the SSB and the density contrast, position and size of the inclusion. For asteroids and comets, large density variations (e.g., porous soil or ice versus solid rock) are relatively easy to detect. The intrinsic spatial resolution of muon radiography (“muography”) is on the scale of a few meters. The spatial resolution that can be achieved in practice depends on signal intensity and integration time (counting statistics), the angular resolution of the muon tracker (hodoscope) and details of data reduction and analysis methodology. Our Phase II project will assess remaining unknowns for the application of muography to determining the interior structure of SSBs, assess risks for implementation, and provide a roadmap for development of SSB muography beyond the NIAC program. To achieve our objectives, we will focus on four interrelated tasks: Task1) Signal and background characterization: Characterize the production and transmission of muons and secondary particle backgrounds made by cosmic ray showers in SSBs; and near-surface features from radiographic and tomographic data; Task2) Imaging studies: Develop methods to determine the density structure of SSB interiors and near-surface features from radiographic and tomographic data; Task3) Instrument design: Using simulations and bench-top laboratory experiments, investigate specific concepts for the design of compact hodoscopes and components; Task4) Synthesis: Combine the results of the first three tasks to determine the range of applicability of the method, identify the steps needed for maturation of the concept, and explore concepts for a pilot muography mission.

Prettyman, Thomas H.↗
NASA NTRS2006

Sensor Management for Applied Research Technologies (SMART)-On Demand Modeling (ODM) Project

NASA requires timely on-demand data and analysis capabilities to enable practical benefits of Earth science observations. However, a significant challenge exists in accessing and integrating data from multiple sensors or platforms to address Earth science problems because of the large data volumes, varying sensor scan characteristics, unique orbital coverage, and the steep learning curve associated with each sensor and data type. The development of sensor web capabilities to autonomously process these data streams (whether real-time or archived) provides an opportunity to overcome these obstacles and facilitate the integration and synthesis of Earth science data and weather model output. A three year project, entitled Sensor Management for Applied Research Technologies (SMART) - On Demand Modeling (ODM), will develop and demonstrate the readiness of Open Geospatial Consortium (OGC) Sensor Web Enablement (SWE) capabilities that integrate both Earth observations and forecast model output into new data acquisition and assimilation strategies. The advancement of SWE-enabled systems (i.e., use of SensorML, sensor planning services - SPS, sensor observation services - SOS, sensor alert services - SAS and common observation model protocols) will have practical and efficient uses in the Earth science community for enhanced data set generation, real-time data assimilation with operational applications, and for autonomous sensor tasking for unique data collection.

Goodman, M.↗
NASA NTRS2017

Reinventing Image Detective: An Evidence-Based Approach to Citizen Science Online

Usability studies demonstrate that web users are notoriously impatient, spending as little as 15 seconds on a home page. How do you get users to stay long enough to understand a citizen science project? How do you get users to complete complex citizen science tasks online? Image Detective, a citizen science project originally developed by scientists and science engagement specialists at the NASA Johnson Space center to engage the public in the analysis of images taken from space by astronauts to help enhance NASA's online database of astronaut imagery, partnered with the CosmoQuest citizen science platform to modernize, offering new and improved options for participation in Image Detective. The challenge: to create a web interface that builds users' skills and knowledge, creating engagement while learning complex concepts essential to the accurate completion of tasks. The project team turned to usability testing for an objective understanding of how users perceived Image Detective and the steps required to complete required tasks. A group of six users was recruited online for unmoderated and initial testing. The users followed a think-aloud protocol while attempting tasks, and were recorded on video and audio. The usability test examined users' perception of four broad areas: the purpose of and context for Image Detective; the steps required to successfully complete the analysis (differentiating images of Earth's surface from those showing outer space and identifying common surface features); locating the image center point on a map of Earth; and finally, naming geographic locations or natural events seen in the image. Usability test findings demonstrated that the following best practices can increase participation in Image Detective and can be applied to the successful implementation of any citizen science project: (1) Concise explanation of the project, its context, and its purpose; (2) Including a mention of the funding agency (in this case, NASA); (3) A preview of the specific tasks required of participants; (4) A dedicated user interface for the actual citizen science interaction. In addition, testing revealed that users may require additional context when a task is complex, difficult, or unusual (locating a specific image and its center point on a map of Earth). Video evidence will be made available with this presentation.

Romano, Cia↗
NASA NTRS2004

Planning for rover opportunistic science

The Mars Exploration Rover Spirit recently set a record for the furthest distance traveled in a single sol on Mars. Future planetary exploration missions are expected to use even longer drives to position rovers in areas of high scientific interest. This increase provides the potential for a large rise in the number of new science collection opportunities as the rover traverses the Martian surface. In this paper, we describe the OASIS system, which provides autonomous capabilities for dynamically identifying and pursuing these science opportunities during longrange traverses. OASIS uses machine learning and planning and scheduling techniques to address this goal. Machine learning techniques are applied to analyze data as it is collected and quickly determine new science gods and priorities on these goals. Planning and scheduling techniques are used to alter the behavior of the rover so that new science measurements can be performed while still obeying resource and other mission constraints. We will introduce OASIS and describe how planning and scheduling algorithms support opportunistic science.

artificial intelligence↗
NASA NTRS2000

The Life Cycle Application of Intelligent Software Modeling for the First Materials Science Research Rack

Marshall Space Flight Center (MSFC) has been funding development of intelligent software models to benefit payload ground operations for nearly a decade. Experience gained from simulator development and real-time monitoring and control is being applied to engineering design, testing, and operation of the First Material Science Research Rack (MSRR-1). MSRR-1 is the first rack in a suite of three racks comprising the Materials Science Research Facility (MSRF) which will operate on the International Space Station (ISS). The MSRF will accommodate advanced microgravity investigations in areas such as the fields of solidification of metals and alloys, thermo-physical properties of polymers, crystal growth studies of semiconductor materials, and research in ceramics and glasses. The MSRR-1 is a joint venture between NASA and the European Space Agency (ESA) to study the behavior of different materials during high temperature processing in a low gravity environment. The planned MSRR-1 mission duration is five (5) years on-orbit and the total design life is ten (IO) years. The MSRR-1 launch is scheduled on the third Utilization Flight (UF-3) to ISS, currently in February of 2003). The objective of MSRR-1 is to provide an early capability on the ISS to conduct material science, materials technology, and space product research investigations in microgravity. It will provide a modular, multi-user facility for microgravity research in materials crystal growth and solidification. An intelligent software model of MSRR-1 is under development and will serve multiple purposes to support the engineering analysis, testing, training, and operational phases of the MSRR-1 life cycle development. The G2 real-time expert system software environment developed by Gensym Corporation was selected as the intelligent system shell for this development work based on past experience gained and the effectiveness of the programming environment. Our approach of multi- uses of the simulation model and its intuitive graphics capabilities is providing a concurrent engineering environment for rapid prototyping and development. Operational schematics of the MSRR-1 electrical, thermal control, vacuum access, and gas supply systems, and furnace inserts are represented graphically in the environment. Logic to represent first order engineering calculations is coded into the knowledge base to simulate the operational behavior of the MSRR-1 systems. An example of engineering data provided includes electrical currents, voltages, operational power, temperatures, thermal fluid flow rates. pressures, and component status indications. These type of data are calculated and displayed at appropriate instrumentation points, and the schematics are animated to reflect the simulated operational status of the MSRR-1. The software control functions are also simulated to represent appropriate operational behavior based on automated control and response to commands received by the crew or ground controllers. The first benefit of this simulation environment is being realized in the high fidelity engineering analysis results from the electrical power system G2 model. Secondly, the MSRR-1 simulation model will be embedded with a hardware mock-up of the MSRR-1 to provide crew training on MSRR-1 integrated payload operations. G2 gateway code will output the simulated instrumentation values, termed as telemetry, in a flight-like data stream so that the crew has realistic and accurate simulated MSRR-1 data on the flight displays which will be designed for crew use. The simulation will also respond appropriately to crew or ground initiated commands, which will be part of normal facility operations. A third use of the G2 model is being planned; the MSRR-1 simulation will be integrated with additional software code as part of the test configuration of the primary onboard computer, or Master Controller, for MSRR-1. We will take advantage of the G2 capability to simulate the flight like data stream to test flight software responses and behavior. A fourth use of the G2 model will be to train the Ground Support Personnel that will monitor the MSRR-1 systems and payloads while they are operating aboard the ISS. The intuitive, schematic based environment will provide an excellent foundation for personnel to understand the integrated configuration and operation of the MSRR-1, and the anticipated telemetry feedback based on operational modes of the equipment. Expert monitoring features will be enhanced to provide a smart monitoring environment for the operators. These features include: (1) Animated, intuitive schematic-based displays which reflect telemetry values, (1) Real-time plotting of simulated or incoming sensor values, (3) High/Low exception monitoring for analog data, (4) Expected state monitoring for discrete data, (5) Data trending, (6) Automated malfunction procedure execution to diagnose problems, (7) Look ahead capability to planned MSRR-1 activities in the onboard timeline. And finally, the logic to calculate telemetry values will be deactivated, and the same environment will interface to the incoming data for the real-time telemetry stream to schematically represent the onboard hardware configuration. G2 will be the foundation for the real-time monitoring and control environment. In summary, our MSRR-1 simulation model spans many elements of the life cycle development of this project: Engineering Analysis, Test and Checkout, Training of Crew and Ground Personnel, and Real-time monitoring and control. By utilizing the unique features afforded by an expert system development environment, we have been able to synergize a powerful tool capable of addressing our project needs at every phase of project development.

Rice, Amanda↗
NASA NTRS2008

The Importance of the International Space Station for Life Sciences Research: Past and Future

The International Space Station (ISS) celebrates ten years of operations in 2008. While the station did not support permanent human crews during the first two years of operations, it hosted a few early science experiments months before the first international crew took up residence in November 2000. Since that time, science returns from the ISS have been growing at a steady pace. To date, early utilization of the U.S. Operating Segment of ISS has fielded nearly 200 experiments for hundreds of ground-based investigators supporting U.S. and international partner research. This paper will summarize the life science accomplishments of early research aboard the ISS both applied human research for exploration, and research on the effects of microgravity on life. At the 10-year point, the scientific returns from ISS should increase at a rapid pace. During the 2008 calendar year, the laboratory space and research facilities (both pressurized and external) will be tripled, with multiple scientific modules that support a wide variety of research racks and science and technology experiments conducted by all of the International Partners. A milestone was reached in February 2008 with the launch and commissioning of ESA s Columbus module and in March of 2008 with the first of three components of the Japanese Kibo laboratory. Although challenges lie ahead, the realization of the international scientific partnership provides new opportunities for scientific collaboration and broadens the research disciplines engaged on ISS. As the ISS nears completion of assembly in 2010, we come to full international utilization of the facilities for research. Using the past as an indicator, we are now able to envision the multidisciplinary contributions to improving life on Earth that the ISS can make as a platform for life sciences research.

Robinson, Julie A.↗
NASA NTRS1988

Exploring the living universe: A strategy for space life sciences

The status and goals of NASA's life sciences programs are examined. Ways and mean for attaining these goals are suggested. The report emphasizes that a stronger life sciences program is imperative if the U.S. space policy is to construct a permanently manned space station and achieve its stated goal of expanding the human presence beyond earth orbit into the solar system. The same considerations apply in regard to the other major goal of life sciences: to study the biological processes and life in the universe. A principal recommendation of the report is for NASA to expand its program of ground- and space-based research contributing to resolving questions about physiological deconditioning, radiation exposure, potential psychological difficulties, and life support requirements that may limit stay times for personnel on the Space Station and complicate missions of more extended duration. Other key recommendations call for strengthening programs of biological systems research in: controlled ecological life support systems for humans in space, earth systems central to understanding the effects on the earth's environment of both natural and human activities, and exobiology.

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NASA NTRSDate not supplied

The NASA DEVELOP Model of Community Science & Engagement: Localizing Earth Science Information

The NASA DEVELOP Program conducts 10 week feasibility studies that apply Earth observation data to address community priorities and support informed decision making. Part of NASA’s Earth Action Capacity Building Program, DEVELOP builds skills in both participants ( recent graduates, and early/transitioning career professionals), who work on small interdisciplinary project teams, and partner organizations (state and local governments, federal agencies, non profit and for profit organizations, universities, and international organizations) that work closely with DEVELOP to design the project. Projects address a wide variety of environmental issues, such as disaster risk and resilience, air pollution, and the impact of urban development, with a growing number of projects exploring how satellite data can help inform decision making around environmental injustices. A subset of DEVELOP partner organizations are local municipalities or community led non profits, with the co production model serving as an effective engagement tool and an introduction for communities to engage in Earth science research and become familiar with satellite remote sensing. This presentation will highlight the DEVELOP co production model, community project use cases, and lessons learned in partnering with local communities.

Michael Pazmino↗
NASA NTRS1989

JPL reuse program

The goal of the JPL reuse activity is to develop a quantitative understanding of the factors which encourage or inhibit software reuse, and of productivity improvements achievable through reuse. The primary activity is the measurement of parameters relevant to reuse in the environment of actual projects. The program has three objectives: (1) to develop a model to allow assessment of competing reuse techniques, (2) to extend reuse from the unit to the sub-system level, and (3) to expand from specific applications to a broader application domain. Application domains, which apply to all interplanetary projects, include Mission Operations, Science Information Systems, Flight Software, and Simulations. The program is targeting all phases and activities of the life cycle and a full range of software products. The approach will be both experimental (observe, hypothesize and evaluate) and constructive (introduce new tools and techniques). The primary target projects are Deep Space Network activities - the Ground Facilities facility upgrade, the Network Operations Control Center upgrade, and the Signal Processing Center. This is the first group of closely related projects being done in Ada at JPL. A reuse base will be developed initially by classifying potentially reusable components from one project; it will be used and expanded with additional projects.

Brown, James W.↗
NASA NTRS1991

Data compression: The end-to-end information systems perspective for NASA space science missions

The unique characteristics of compressed data have important implications to the design of space science data systems, science applications, and data compression techniques. The sequential nature or data dependence between each of the sample values within a block of compressed data introduces an error multiplication or propagation factor which compounds the effects of communication errors. The data communication characteristics of the onboard data acquisition, storage, and telecommunication channels may influence the size of the compressed blocks and the frequency of included re-initialization points. The organization of the compressed data are continually changing depending on the entropy of the input data. This also results in a variable output rate from the instrument which may require buffering to interface with the spacecraft data system. On the ground, there exist key tradeoff issues associated with the distribution and management of the science data products when data compression techniques are applied in order to alleviate the constraints imposed by ground communication bandwidth and data storage capacity.

Tai, Wallace↗
NASA NTRS1990

Advanced program development management software system. Software description and user's manual

The objectives of this project were to apply emerging techniques and tools from the computer science discipline of paperless management to the activities of the Space Transportation and Exploration Office (PT01) in Marshall Space Flight Center (MSFC) Program Development, thereby enhancing the productivity of the workforce, the quality of the data products, and the collection, dissemination, and storage of information. The approach used to accomplish the objectives emphasized the utilization of finished form (off-the-shelf) software products to the greatest extent possible without impacting the performance of the end product, to pursue developments when necessary in the rapid prototyping environment to provide a mechanism for frequent feedback from the users, and to provide a full range of user support functions during the development process to promote testing of the software.

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