Results for “science data processing” — Page 96

NASA NTRS1973

Development of flight experiment work performance and workstation interface requirements, part 1. Technical report and appendices A through G

A skill requirement definition method was applied to the problem of determining, at an early stage in system/mission definition, the skills required of on-orbit crew personnel whose activities will be related to the conduct or support of earth-orbital research. The experiment data base was selected from proposed experiments in NASA's earth orbital research and application investigation program as related to space shuttle missions, specifically those being considered for Sortie Lab. Concepts for two integrated workstation consoles for Sortie Lab experiment operations were developed, one each for earth observations and materials sciences payloads, utilizing a common supporting subsystems core console. A comprehensive data base of crew functions, operating environments, task dependencies, task-skills and occupational skills applicable to a representative cross section of earth orbital research experiments is presented. All data has been coded alphanumerically to permit efficient, low cost exercise and application of the data through automatic data processing in the future.

Hatterick, R. G.↗

NASA NTRS1986

Global energetics analysis using 3-dimensional normal mode decomposition

The Goddard Laboratory for Atmospheric Sciences (GLAS) analysis of the FGGE observations for a 25-day period in January 1979 is examined using the normal mode energetics scheme. The results from the energetics analysis are compared with the data of Tanaka (1985). Kinetic energy spectra of the barotropic mode in the meridional-mode and frequency domains, and the total diabatic process are studied. It is observed that there are significant differences between GLAS and GFDL analyses results in the barotropic energy of gravity modes and the normal energetics scheme is applicable as a diagnostic tool.

Tanaka, Hiroshi↗

NASA NTRS1989

SHARP: A multi-mission AI system for spacecraft telemetry monitoring and diagnosis

The Spacecraft Health Automated Reasoning Prototype (SHARP) is a system designed to demonstrate automated health and status analysis for multi-mission spacecraft and ground data systems operations. Telecommunications link analysis of the Voyager II spacecraft is the initial focus for the SHARP system demonstration which will occur during Voyager's encounter with the planet Neptune in August, 1989, in parallel with real-time Voyager operations. The SHARP system combines conventional computer science methodologies with artificial intelligence techniques to produce an effective method for detecting and analyzing potential spacecraft and ground systems problems. The system performs real-time analysis of spacecraft and other related telemetry, and is also capable of examining data in historical context. A brief introduction is given to the spacecraft and ground systems monitoring process at the Jet Propulsion Laboratory. The current method of operation for monitoring the Voyager Telecommunications subsystem is described, and the difficulties associated with the existing technology are highlighted. The approach taken in the SHARP system to overcome the current limitations is also described, as well as both the conventional and artificial intelligence solutions developed in SHARP.

Lawson, Denise L.↗

NASA NTRS1990

Applications of ISES for vegetation and land use

Remote sensing relative to applications involving vegetation cover and land use is reviewed to consider the potential benefits to the Earth Observing System (Eos) of a proposed Information Sciences Experiment System (ISES). The ISES concept has been proposed as an onboard experiment and computational resource to support advanced experiments and demonstrations in the information and earth sciences. Embedded in the concept is potential for relieving the data glut problem, enhancing capabilities to meet real-time needs of data users and in-situ researchers, and introducing emerging technology to Eos as the technology matures. These potential benefits are examined in the context of state-of-the-art research activities in image/data processing and management.

Wilson, R. Gale↗

NASA NTRS1989

SHARP - A multi-mission AI system for spacecraft telemetry monitoring and diagnosis

The Spacecraft Health Automated Reasoning Prototype (SHARP) is a system designed to demonstrate automated health and status analysis for multi-mission spacecraft and ground data systems operations. Telecommunications link analysis of the Voyager II spacecraft is the initial focus for the SHARP system demonstration which will occur during Voyager's encounter with the planet Neptune in August, 1989, in parallel with real-time Voyager operations. The SHARP system combines conventional computer science methodologies with artificial intelligence techniques to produce an effective method for detecting and analyzing potential spacecraft and ground systems problems. The system performs real-time analysis of spacecraft and other related telemetry, and is also capable of examining data in historical context. A brief introduction is given to the spacecraft and ground systems monitoring process at the Jet Propulsion Laboratory. The current method of operation for monitoring the Voyager Telecommunications subsystem is described, and the difficulties associated with the existing technology are highlighted. The approach taken in the SHARP system to overcome the current limitations is also described, as well as both the conventional and artificial intelligence solutions developed in SHARP.

Lawson, Denise L.↗

NASA NTRS1989

Cross-fertilization between connectionist networks and highly parallel architectures

The theoretical and practical connections between connectionist schemes such as neural-network computers and traditional symbolic processing architectures involving a high degree of parallelism are explored, reviewing the results of recent investigations. Topics addressed include data flow, data structure, and control flow; conventional pointers; associative addressing; hashing and reduced representations; the problem of binding values to variables; and levels of parallelism. It is concluded that connectionism is more closely related to traditional computer science and technology than is generally admitted; more cooperation between followers of the two approaches is recommended.

Barnden, John↗

NASA NTRS1993

The Mars Aerial Platform (MAP) mission

The Mars Aerial Platform (MAP) mission is a conceptual design for a low-cost, Discovery-class mission whose purpose would be to generate tens of thousands of very-high-resolution (20 cm/pixel) pictures of the martian surface, map the global circulation of the martian atmosphere, and examine the surface and subsurface with ground-penetrating radar, infrared spectroscopy, neutron spectroscopy, and other remote sensing techniques. The data would be acquired by instruments that are carried by balloons flying at a nominal altitude of about 7 km over the martian surface. Because new balloon and microspacecraft technology is now available, the balloon probes could be quite long-lived, lasting hundreds or even thousands of days, producing an immense science harvest in the process. Together with the Mars Environmental Survey (MESUR) surface network science mission, MAP would revolutionize our knowledge of the Red Planet.

Zubrin, R.↗

NASA NTRS1994

In-flight scale/distortion calibration of the Hubble Space Telescope fixed-head star trackers

This paper describes an in-flight scale and distortion calibration procedure that has been developed for the Ball Aerospace Systems Division Fixed-Head Star Trackers (FHST's) used on the Hubble Space Telescope (HST). The FHST is a magnetically focused and deflected imaging sensor that is designed to track stars as faint as m(sub v) = 5.7 over an 8 degree by 8 degree field of view. Raw FHST position measurements are accurate to approximately 200 arcseconds, but this can be improved to 10-15 arcseconds by processing the raw measurements through calibration polynomials that correct for flat field, temperature intensity, and magnetic field effects. The coefficients for these polynomials were initially determined using ground test data. On HST the use of three FHST's is an integral part of the preliminary attitude update procedures required before the acquisition of guide stars for science observations. To this end, FHST-based attitude determination having single-axis errors no worse than 22 arcseconds (1 sigma) is required. In early 1991 it became evident that one of the HST FHST's was experiencing a significant change in its optical scale. By mid-1993 the size of this error had grown to a point that, if not corrected, it would correspond to a maximum position error on the order of 100 arcseconds. Subsequent investigations demonstrated that substantial, uncompensated cubic distortion effects had also developed, the maximum contribution to position errors from the cubic terms being on the order of 30 arcseconds. To ensure accurate FHST-based attitude updates, procedures have been developed to redetermine the FHST scale and distortion calibration coefficients based on in-flight data gathered during normal HST operations. These scale and distortion calibrations have proven very effective operationally, and procedures are in place to monitor FHST calibration changes on a continuing basis.

Mccutcheon, R.↗

NASA NTRS1994

What would we miss if we characterized the Moon and Mars with just planetary meteorites, remote mapping, and robotic landers?

Exploration of the Moon and planets began with telescopic studies of their surfaces, continued with orbiting spacecraft and robotic landers, and will culminate with manned exploration and sample return. For the Moon and Mars we also have accidental samples provided by impacts on their surfaces, the lunar and martian meteorites. How much would we know about the lunar surface if we only had lunar meteorites, orbital spacecraft, and robotic exploration, and not the Apollo and Luna returned samples? What does this imply for Mars? With martian meteorites and data from Mariner, Viking, and the future Pathfinder missions, how much could we learn about Mars? The basis of most of our detailed knowledge about the Moon is the Apollo samples. They provide ground truth for the remote mapping, timescales for lunar processes, and samples from the lunar interior. The Moon is the foundation of planetary science and the basis for our interpretation of the other planets. Mars is similar to the Moon in that impact and volcanism are the dominant processes, but Mars' surface has also been affected by wind and water, and hence has much more complex surface geology. Future geochemical or mineralogical mapping of Mars' surface should be able to tell us whether the dominant rock types of the ancient southern highlands are basaltic, anorthositic, granitic, or something else, but will not be able to tell us the detailed mineralogy, geochemistry, or age. Without many more martian meteorites or returned samples we will not know the diversity of martian rocks, and therefore will be limited in our ability to model martian geological evolution.

Lindstrom, M. M.↗

NASA NTRS1999

Zero Gravity Research Facility User's Guide

The Zero Gravity Research Facility (ZGF) is operated by the Space Experiments Division of the NASA John H. Glenn Research Center (GRC) for investigators sponsored by the Microgravity Science and Applications Division of NASA Headquarters. This unique facility has been utilized by scientists and engineers for reduced gravity experimentation since 1966. The ZGF has provided fundamental scientific information, has been used as an important test facility in the space flight hardware design, development, and test process, and has also been a valuable source of data in the flight experiment definition process. The purpose of this document is to provide information and guidance to prospective researchers regarding the design, buildup, and testing of microgravity experiments.

Thompson, Dennis M.↗

NASA NTRS1997

Review of Galileo Probe Entry Technology

This talk is a review of the Galileo entry mission with a focus on entry technology, not planetary science. A general description of the mission, entry parameters, and entry vehicle are provided, followed by a more detailed description of the vehicle heatshield shape, size, materials, and instrumentation. The heat shield design tools and process are discussed wish emphasis on the issues and challenges which were faced and the role of ground test facilities. Flight data are compared with the preflight predictions. What have we learned?

Milos, Frank S.↗

NASA NTRS2001

Tropical Rainfall Measuring Mission: Monitoring the Global Tropics for 3 Years and Beyond

The Tropical Rainfall Measuring Mission (TRMM) was launched in November 1997 as a joint U.S.-Japanese mission to advance understanding of the global energy and water cycle by providing distributions of rainfall and latent heating over the global tropics. As a part of NASA's Earth System Enterprise, TRMM seeks to understand the mechanisms through which changes in tropical rainfall influence global circulation. Additionally, a goal is to improve the ability to model these processes in order to predict global circulations and rainfall variability at monthly and longer time scales. Such understanding has implications for assessing climate processes related to El Nino/La Nina and Global Warming. TRMM has also provided unexpected and exciting new knowledge and applications in areas related to hurricane monitoring, lightning, pollution, hydrology, and other areas. This CD-ROM includes a self-contained PowerPoint presentation that provides an overview of TRMM and significant science results; a set of data movies or animation; and listings of current TRMM-related publications in the literature.

Shepherd, Marshall↗

NASA NTRS2005

Spatial Scaling of Snow Observations and Microwave Emission Modeling During CLPX and Appropriate Satellite Sensor Resolution

Accurate estimates of snow water equivalent and other properties play an important role in weather, natural hazard, and hydrological forecasting and climate modeling over a range of scales in space and time. Remote sensing-derived estimates have traditionally been of the "snapshot" type, but techniques involving models with assimilation are also being explored. In both cases, forward emission models are useful to understand the observed passive microwave signatures and developing retrieval algorithms. However, mismatches between passive microwave sensor resolutions and the scales of processes controlling subpixel heterogeneity can affect the accuracy of the estimates. Improving the spatial resolution of new passive microwave satellite sensors is a major desire in order to (literally) resolve such subpixel heterogeneity, but limited spacecraft and mission resources impose severe constraints and tradeoffs. In order to maximize science return while mitigating risk for a satellite concept, it is essential to understand the scaling behavior of snow in terms of what the sensor sees (brightness temperature) as well as in terms of the actual variability of snow. NASA's Cold Land Processes Experiment-1 (CLPX-1: Colorado, 2002 and 2003) was designed to provide data to measure these scaling behaviors for varying snow conditions in areas with forested, alpine, and meadow/pasture land cover. We will use observations from CLPX-1 ground, airborne, and satellite passive microwave sensors to examine and evaluate the scaling behavior of observed and modeled brightness temperatures and observed and retrieved snow parameters across scales from meters to 10's of kilometers. The conclusions will provide direct examples of the appropriate spatial sampling scales of new sensors for snow remote sensing. The analyses will also illustrate the effects and spatial scales of the underlying phenomena (e.g., land cover) that control subpixel heterogeneity.

Kim, Edward J.↗

NASA NTRS2010

Linking Indigenous Knowledge and Observed Climate Change Studies

We present indigenous knowledge narratives and explore their connections to documented temperature and other climate changes and observed climate change impact studies. We then propose a framework for enhancing integration of these indigenous narratives of observed climate change with global assessments. Our aim is to contribute to the thoughtful and respectful integration of indigenous knowledge with scientific data and analysis, so that this rich body of knowledge can inform science, and so that indigenous and traditional peoples can use the tools and methods of science for the benefit of their communities if they choose to do so. Enhancing ways of understanding such connections are critical as the Intergovernmental Panel on Climate Change Fifth Assessment process gets underway.

Alexander, Chief Clarence↗

NASA NTRS2011

Feature Acquisition with Imbalanced Training Data

This work considers cost-sensitive feature acquisition that attempts to classify a candidate datapoint from incomplete information. In this task, an agent acquires features of the datapoint using one or more costly diagnostic tests, and eventually ascribes a classification label. A cost function describes both the penalties for feature acquisition, as well as misclassification errors. A common solution is a Cost Sensitive Decision Tree (CSDT), a branching sequence of tests with features acquired at interior decision points and class assignment at the leaves. CSDT's can incorporate a wide range of diagnostic tests and can reflect arbitrary cost structures. They are particularly useful for online applications due to their low computational overhead. In this innovation, CSDT's are applied to cost-sensitive feature acquisition where the goal is to recognize very rare or unique phenomena in real time. Example applications from this domain include four areas. In stream processing, one seeks unique events in a real time data stream that is too large to store. In fault protection, a system must adapt quickly to react to anticipated errors by triggering repair activities or follow- up diagnostics. With real-time sensor networks, one seeks to classify unique, new events as they occur. With observational sciences, a new generation of instrumentation seeks unique events through online analysis of large observational datasets. This work presents a solution based on transfer learning principles that permits principled CSDT learning while exploiting any prior knowledge of the designer to correct both between-class and withinclass imbalance. Training examples are adaptively reweighted based on a decomposition of the data attributes. The result is a new, nonparametric representation that matches the anticipated attribute distribution for the target events.

Thompson, David R.↗

NASA NTRS2014

Lightning Imaging Sensor (LIS) for the International Space Station (ISS): Mission Description and Science Goals

In recent years, NASA Marshall Space Flight Center, the University of Alabama in Huntsville, and their partners have developed and demonstrated space-based lightning observations as an effective remote sensing tool for Earth science research and applications. The Lightning Imaging Sensor (LIS) on the Tropical Rainfall Measuring Mission (TRMM) continues to provide global observations of total lightning after 17 years on-orbit. In April 2013, a space-qualified LIS built as the flight spare for TRMM, was selected for flight as a science mission on the International Space Station. The ISS LIS (or I-LIS as Hugh Christian prefers) will be flown as a hosted payload on the Department of Defense Space Test Program (STP) H5 mission, which has a January 2016 baseline launch date aboard a SpaceX launch vehicle for a 2-4 year or longer mission. The LIS measures the amount, rate, and radiant energy of global lightning. More specifically, it measures lightning during both day and night, with storm scale resolution, millisecond timing, and high, uniform detection efficiency, without any land-ocean bias. Lightning is a direct and most impressive response to intense atmospheric convection. It has been found that the characteristics of lightning that LIS measures can be quantitatively coupled to both thunderstorm and other geophysical processes. Therefore, the ISS LIS lightning observations will provide important gap-filling inputs to pressing Earth system science issues across a broad range of disciplines, including weather, climate, atmospheric chemistry, and lightning physics. A unique contribution from the ISS platform will be the availability of real-time lightning, especially valuable for operational applications over data sparse regions such as the oceans. The ISS platform will also uniquely enable LIS to provide simultaneous and complementary observations with other payloads such as the European Space Agency's Atmosphere-Space Interaction Monitor (ASIM) that will be exploring the connection between thunderstorms and lightning with terrestrial gamma-ray flashes (TGFs). Another important function of the ISS LIS will be to provide cross-sensor calibration/validation with a number of other payloads, including the TRMM LIS and the next generation geostationary lightning mappers (e.g., GOES-R Geostationary Lightning Mapper and Meteosat Third Generation Lightning Imager). This inter-calibration will improve the long term climate monitoring provided by all these systems. Finally, the ISS LIS will extend the time-series climate record of LIS lightning observations and expand the latitudinal coverage of LIS lightning to the climate significant upper middle-latitudes.

Blakeslee, R. J.↗

NASA NTRS2014

Lightning Imaging Sensor (LIS) for the International Space Station (ISS): Mission Description and Science Goals

In recent years, NASA Marshall Space Flight Center, the University of Alabama in Huntsville, and their partners have developed and demonstrated space-based lightning observations as an effective remote sensing tool for Earth science research and applications. The Lightning Imaging Sensor (LIS) on the Tropical Rainfall Measuring Mission (TRMM) continues to provide global observations of total lightning after 17 years on-orbit. In April 2013, a space-qualified LIS built as the flight spare for TRMM, was selected for flight as a science mission on the International Space Station. The ISS LIS (or I-LIS as Hugh Christian prefers) will be flown as a hosted payload on the Department of Defense Space Test Program (STP) H5 mission, which has a January 2016 baseline launch date aboard a SpaceX launch vehicle for a 2-4 year or longer mission. The LIS measures the amount, rate, and radiant energy of global lightning. More specifically, it measures lightning during both day and night, with storm scale resolution, millisecond timing, and high, uniform detection efficiency, without any land-ocean bias. Lightning is a direct and most impressive response to intense atmospheric convection. It has been found that the characteristics of lightning that LIS measures can be quantitatively coupled to both thunderstorm and other geophysical processes. Therefore, the ISS LIS lightning observations will provide important gap-filling inputs to pressing Earth system science issues across a broad range of disciplines, including weather, climate, atmospheric chemistry, and lightning physics. A unique contribution from the ISS platform will be the availability of real-time lightning, especially valuable for operational applications over data sparse regions such as the oceans. The ISS platform will also uniquely enable LIS to provide simultaneous and complementary observations with other payloads such as the European Space Agency's Atmosphere-Space Interaction Monitor (ASIM) that will be exploring the connection between thunderstorms and lightning with terrestrial gamma-ray flashes (TGFs). Another important function of the ISS LIS will be to provide cross-sensor calibration/validation with a number of other payloads, including the TRMM LIS and the next generation geostationary lightning mappers (e.g., GOES-R Geostationary Lightning Mapper and Meteosat Third Generation Lightning Imager). This inter-calibration will improve the long term climate monitoring provided by all these systems. Finally, the ISS LIS will extend the time-series climate record of LIS lightning observations and expand the latitudinal coverage of LIS lightning to the climate significant upper middle-latitudes.

Blakeslee, R. J.↗

NASA NTRS2018

Digital Beamforming Based RFI Mitigation for Synthetic Aperture Radar

An increasing challenge for P-band Synthetic Aperture Radar (SAR) is Radio Frequency Interference (RFI). RFI results in image distortions and degrades the derived science products. This makes it critical to apply RFI removal techniques to restore the image quality. New advanced techniques can be achieved with Digital Beamforming (DBF) radars such as EcoSAR. In this paper, we present a Range-Dependent Time Minimum Variance Distortionless Response (RDTMVDR) Beamformer and apply it to EcoSAR flight data during post-processing. The antenna pattern (AP) is adaptively changed for each range line which increases the RFI suppression compared to a fixed AP for each pulse. The interferometric image quality is assessed before and after RFI suppression.

Bollian, Tobias↗