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At least 1,279 records · Page 71
All sourcesNASA NTRSDOE OSTI
NASA NTRS2000

An Unmanned Spacecraft Subsystem Cost Model for Advance Mission Planning

This paper reports on the development of a parametric cost model that is being built at JPL to estimate costs of future, deep space, robotic science missions. Because of the changes in the mission implementation process and technology changes, the model is being built in a dramatically different manner than past models which have had access to a data base that drew heavily on the correlation between mass and actual costs.

Parametric↗
NASA NTRSDate not supplied

Big-data Efficient and Automated Science Transfer (BEAST): An Open-Source Software Architecture for Arc Jet Data Management, Modeling, and Automation

Big-data Efficient and Automated Science Transfer (BEAST) is a facility data management application developed for the NASA Ames arc jet facilities. The current decentralized data management practices limit statistical tracking, synchronization between video/time series, search capability, data throughput, and data processing speed/efficiency. Consequently, BEAST was developed to provide a new data infrastructure with streamlined data collection, processing, transfer, and analysis. This new framework also seeks to implement the FAIR principles of data stewardship: Findable, Accessible, Interoperable, and Reusable. The BEAST framework is based on a combination of the Python Django web framework and the Python data stack to provide a monolithic, open-source platform for data management, automation, and machine learning. This architecture was chosen for maintainability and scalability for a small, in-house development team. This paper will describe the application framework, deployment, and discuss the benefits and future plans for the system.

Data management↗
NASA NTRSDate not supplied

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

RadLab, a new component of the NASA Open Science Data Repository (OSDR), is a platform built upon a database of radiation data relevant to space biology. RadLab provides visual and programmatic interfaces for interrogation of its database, as well as a submission process for inclusion of data from investigators. The RadLab application programming interface (API) implements a request syntax enabling users to retrieve data filtered by various combinations of parameters (detector type, location, direction, timespan, etc), which are delivered in machine-readable text formats, ready to be ingested by downstream analysis pipelines; while the graphical user interface (GUI) provides easy means to iteratively modify query parameters and incorporates a number of standard analyses and visualizations (time series plots, geospatial visualizations, detector comparison). Investigators from many countries, including US, Russia, Japan, Canada, the Czech Republic, Germany, Hungary, and Italy, have committed to provide data from their instruments located on the ISS; RadLab will also include data from other spacecraft in LEO (e.g., the Space Shuttle, the Mir space station), BLEO (e. g. BioSentinel, Mars Orbiter, among others), and on other celestial bodies (e. g. Chang’e 4, Curiosity). The first release of RadLab has been made available to the public. Once fully operational, RadLab will provide a comprehensive and ever-growing compendium of space radiation data, facilitating straightforward access to multiple types of readings and enabling space biology researchers to perform intercomparisons of detectors and to determine the radiation environment of research missions, both via programmatic retrieval of these data and via the graphical analysis toolkit; as well as a user-friendly submission portal for ingesting data from space agencies and research institutions. Radiation scientists will be able to use RadLab to gain a deeper understanding of the space radiation environment for future human space exploration. The RadLab Working Group has been formed to foster close collaborations among data contributors and users, to identify data sources, to put in place standards for data normalization, to guide the development of features of the analysis toolkit, to establish the use of RadLab in space radiation biology research, and eventually to provide a forum for discussing relevant research issues that can take advantage of RadLab's capabilities.

radiation↗
NASA NTRS2001

The International Space Station human life sciences experiment implementation process

The selection, definition, and development phases of a Life Sciences flight research experiment has been consistent throughout the past decade. The implementation process, however, has changed significantly within the past two years. This change is driven primarily by the shift from highly integrated, dedicated research missions on platforms with well defined processes to self contained experiments with stand alone operations on platforms which are being concurrently designed. For experiments manifested on the International Space Station (ISS) and/or on short duration missions, the more modular, streamlined, and independent the individual experiment is, the more likely it is to be successfully implemented before the ISS assembly is completed. During the assembly phase of the ISS, science operations are lower in priority than the construction of the station. After the station has been completed, it is expected that more resources will be available to perform research. The complexity of implementing investigations increases with the logistics needed to perform the experiment. Examples of logistics issues include- hardware unique to the experiment; large up and down mass and volume needs; access to crew and hardware during the ascent or descent phases; maintenance of hardware and supplies with a limited shelf life,- baseline data collection schedules with lengthy sessions or sessions close to the launch or landing; onboard stowage availability, particularly cold stowage; and extensive training where highly proficient skills must be maintained. As the ISS processes become better defined, experiment implementation will meet new challenges due to distributed management, on-orbit resource sharing, and adjustments to crew availability pre- and post-increment. c 2001. Elsevier Science Ltd. All rights reserved.

Research↗
NASA NTRS2005

Algorithm Science to Operations for the National Polar-orbiting Operational Environmental Satellite System (NPOESS) Visible/Infrared Imager/Radiometer Suite (VIIRS)

The VIIRS sensor provides measurements for 22 Environmental Data Records (EDRs) addressing the atmosphere, ocean surface temperature, ocean color, land parameters, aerosols, imaging for clouds and ice, and more. That is, the VIIRS collects visible and infrared radiometric data of the Earth's atmosphere, ocean, and land surfaces. Data types include atmospheric, clouds, Earth radiation budget, land/water and sea surface temperature, ocean color, and low light imagery. This wide scope of measurements calls for the preparation of a multiplicity of Algorithm Theoretical Basis Documents (ATBDs), and, additionally, for intermediate products such as cloud mask, et al. Furthermore, the VIIRS interacts with three or more other sensors. This paper addresses selected and crucial elements of the process being used to convert and test an immense volume of a maturing and changing science code to the initial operational source code in preparation for launch of NPP. The integrity of the original science code is maintained and enhanced via baseline comparisons when re-hosted, in addition to multiple planned code performance reviews.

NPOESS (NATIONAL POLAR-ORBITING OPERATIONAL ENVIRO↗
NASA NTRS2011

Calibrated Noise Measurements with Induced Receiver Gain Fluctuations

The lack of well-developed techniques for modeling changing statistical moments in our observations has stymied the application of stochastic process theory in science and engineering. These limitations were encountered when modeling the performance of radiometer calibration architectures and algorithms in the presence of non stationary receiver fluctuations. Analyses of measured signals have traditionally been limited to a single measurement series. Whereas in a radiometer that samples a set of noise references, the data collection can be treated as an ensemble set of measurements of the receiver state. Noise Assisted Data Analysis is a growing field of study with significant potential for aiding the understanding and modeling of non stationary processes. Typically, NADA entails adding noise to a signal to produce an ensemble set on which statistical analysis is performed. Alternatively as in radiometric measurements, mixing a signal with calibrated noise provides, through the calibration process, the means to detect deviations from the stationary assumption and thereby a measurement tool to characterize the signal's non stationary properties. Data sets comprised of calibrated noise measurements have been limited to those collected with naturally occurring fluctuations in the radiometer receiver. To examine the application of NADA using calibrated noise, a Receiver Gain Modulation Circuit (RGMC) was designed and built to modulate the gain of a radiometer receiver using an external signal. In 2010, an RGMC was installed and operated at the National Institute of Standards and Techniques (NIST) using their Noise Figure Radiometer (NFRad) and national standard noise references. The data collected is the first known set of calibrated noise measurements from a receiver with an externally modulated gain. As an initial step, sinusoidal and step-function signals were used to modulate the receiver gain, to evaluate the circuit characteristics and to study the performance of a variety of calibration algorithms. The receiver noise temperature and time-bandwidth product of the NFRad are calculated from the data. Statistical analysis using temporal-dependent calibration algorithms reveals that the natural occurring fluctuations in the receiver are stationary over long intervals (100s of seconds); however the receiver exhibits local non stationarity over the interval over which one set of reference measurements are collected. A variety of calibration algorithms have been applied to the data to assess algorithms' performance with the gain fluctuation signals. This presentation will describe the RGMC, experiment design and a comparative analysis of calibration algorithms.

Racette, Paul↗
NASA NTRS2004

Caltrans Keeps the Spitzer Pipelines Moving

The computer pipelines used to process digital infrared astronomical images from NASA's Spitzer Space Telescope require various input calibration-data files for characterizing the attributes and behaviors of the onboard focal-plane-arrays and their detector pixels, such as operability, dark-current offset, linearity, non- uniformity, muxbleed, droop, and point-response functions. The telescope has three very different science instruments, each with three or four spectral-band-pass channels, depending on the instrument. Moreover, each instrument has various operating modes (e-g., full array or sub-array in one case) and parameters (e.g., integration time). Calibration data that depend on these considerations are needed by pipelines for generating both science products (production pipelines) and higher-level calibration products (calibration pipelines). The calibration files are created in various formats either 'off-line' or by the aforementioned calibration pipelines, depending on the above configuration details. Also, the calibration files are generally applicable to a certain time period and therefore must be selected accordingly for a given raw input image to be correctly processed. All of this complexity in selecting and retrieving calibration files for pipeline processing is handled by a procedural software-program called 'caltrans' . This software, which is implemented in C and interacts with an Informix database, was developed at the Spitzer Science Center (SSC) and is now deployed in SSC daily operations. The software is rule-based, very flexible, and, for efficiency, capable of retrieving multiple calibration files with a single software-execution command.

Spitzer↗
NASA NTRS2020

PHALANX: Expendable Projectile Sensor Networks for Planetary Exploration

Technologies enabling long-term, wide-ranging measurement in hard-to-reach areas are a critical need for planetary science inquiry. Phenomena of interest include flows or variations in volatiles, gas composition or concentration, particulate density, or even simply temperature. Improved measurement of these processes enables understanding of exotic geologies and distributions or correlating indicators of trapped water or biological activity. However, such data is often needed in unsafe areas such as caves, lava tubes, or steep ravines not easily reached by current spacecraft and planetary robots. To address this capability gap, we have developed miniaturized, expendable sensors which can be ballistically lobbed from a robotic rover or static lander - or even dropped during a flyover. These projectiles can perform sensing during flight and after anchoring to terrain features. By augmenting exploration systems with these sensors, we can extend situational awareness, perform long-duration monitoring, and reduce utilization of primary mobility resources, all of which are crucial in surface missions. We call the integrated payload that includes a cold gas launcher, smart projectiles, planning software, network discovery, and science sensing: PHALANX. In this paper, we introduce the mission architecture for PHALANX and describe an exploration concept that pairs projectile sensors with a rover “mothership.” Science use cases explored include reconnaissance using ballistic cameras, volatiles detection, and building timelapse maps of temperature and illumination conditions. Strategies to autonomously coordinate constellations of deployed sensors to self-discover and localize with peer ranging (i.e. a “local GPS”) are summarized, thus providing communications infrastructure beyond-line-of-sight (BLOS) of the rover. Capabilities were demonstrated through both simulation and physical testing with a terrestrial prototype. The approach to developing a terrestrial prototype is discussed, including design of the launching mechanism, projectile optimization, micro-electronics fabrication, and sensor selection. Results from early testing and characterization of commercial-off-the-shelf (COTS) components are reported. Nodes were subjected to successful burn-in tests over 48 hours at full logging duty cycle. Integrated field tests were conducted in the Roverscape, a half-acre planetary analog environment at NASA Ames, where we tested up to 10 sensor nodes simultaneously coordinating with an exploration rover. Ranging accuracy has been demonstrated to be within +/-10cm over 20m using commodity radios when compared to high-resolution laser scanner ground truthing. Evolution of the design, including progressive miniaturization of the electronics and iterated modifications of the enclosure housing for streamlining and optimized radio performance are described. Finally, lessons learned to date, gaps toward eventual flight mission implementation, and continuing future development plans are discussed.

Dille, Michael↗
NASA NTRS2014

Use of Semantic Technology to Create Curated Data Albums

One of the continuing challenges in any Earth science investigation is the discovery and access of useful science content from the increasingly large volumes of Earth science data and related information available online. Current Earth science data systems are designed with the assumption that researchers access data primarily by instrument or geophysical parameter. Those who know exactly the data sets they need can obtain the specific files using these systems. However, in cases where researchers are interested in studying an event of research interest, they must manually assemble a variety of relevant data sets by searching the different distributed data systems. Consequently, there is a need to design and build specialized search and discover tools in Earth science that can filter through large volumes of distributed online data and information and only aggregate the relevant resources needed to support climatology and case studies. This paper presents a specialized search and discovery tool that automatically creates curated Data Albums. The tool was designed to enable key elements of the search process such as dynamic interaction and sense-making. The tool supports dynamic interaction via different modes of interactivity and visual presentation of information. The compilation of information and data into a Data Album is analogous to a shoebox within the sense-making framework. This tool automates most of the tedious information/data gathering tasks for researchers. Data curation by the tool is achieved via an ontology-based, relevancy ranking algorithm that filters out nonrelevant information and data. The curation enables better search results as compared to the simple keyword searches provided by existing data systems in Earth science.

Ramachandran, Rahul↗
NASA NTRS2013

Filter Strategies for Mars Science Laboratory Orbit Determination

The Mars Science Laboratory (MSL) spacecraft had ambitious navigation delivery and knowledge accuracy requirements for landing inside Gale Crater. Confidence in the orbit determination (OD) solutions was increased by investigating numerous filter strategies for solving the orbit determination problem. We will discuss the strategy for the different types of variations: for example, data types, data weights, solar pressure model covariance, and estimating versus considering model parameters. This process generated a set of plausible OD solutions that were compared to the baseline OD strategy. Even implausible or unrealistic results were helpful in isolating sensitivities in the OD solutions to certain model parameterizations or data types.

Mars Science Laboratory (MSL)↗
NASA NTRS2011

An Integrated Hydrological and Water Management Study of the Entire Nile River System - Lake Victoria to Nile Delta

The Nile basin River system spans 3 million km(exp 2) distributed over ten nations. The eight upstream riparian nations, Ethiopia, Eretria, Uganda, Rwanda, Burundi, Congo, Tanzania and Kenya are the source of approximately 86% of the water inputs to the Nile, while the two downstream riparian countries Sudan and Egypt, presently rely on the river's flow for most of the their needs. Both climate and agriculture contribute to the complicated nature of Nile River management: precipitation in the headwaters regions of Ethiopia and Lake Victoria is variable on a seasonal and inter-annual basis, while demand for irrigation water in the arid downstream region is consistently high. The Nile is, perhaps, one of the most difficult trans-boundary water issue in the world, and this study would be the first initiative to combine NASA satellite observations with the hydrologic models study the overall water balance in a to comprehensive manner. The cornerstone application of NASA's Earth Science Research Results under this project are the NASA Land Data Assimilation System (LDAS) and the USDA Atmosphere-land Exchange Inverse (ALEXI) model. These two complementary research results are methodologically independent methods for using NASA observations to support water resource analysis in data poor regions. Where an LDAS uses multiple sources of satellite data to inform prognostic simulations of hydrological process, ALEXI diagnoses evapotranspiration and water stress on the basis of thermal infrared satellite imagery. Specifically, this work integrates NASA Land Data Assimilation systems into the water management decision support systems that member countries of the Nile Basin Initiative (NBI) and Regional Center for Mapping of Resources for Development (RCMRD, located in Nairobi, Kenya) use in water resource analysis, agricultural planning, and acute drought response to support sustainable development of Nile Basin water resources. The project is motivated by the recognition that accurate, frequent, and spatially distributed estimates of the water balance are necessary for effective water management. This creates a challenge for watersheds that are large, include data poor regions, and/or span multiple nations. All of these descriptors apply to the Nile River basin, yet successful management of the Nile is critical for development and political stability in the region. For this reason, improved hydrological data to support cooperative water management in the Nile basin is a priority for USAID, the US State Department, the World Bank and other international organizations. In this project, the U.S. based research team is working with partners at RCMRD, Nile Basin Initiative (NBI), and their member national-level agencies to develop satellite-based land cover maps, satellite-derived evapotranspiration estimates (using the ALEXI algorithm), and NASA's Land Data Assimilation System (LDAS) customized to match identified information needs. The cornerstone applied sciences product of the project is the development of a customized "Nile LDAS" that will produce optimal estimates of hydrological states and fluxes, as vetted against the in situ observations of NBI and RCMRD member organizations and independent satellite-derived hydrological estimates. Nile LDAS will be applied to improve the reliability of emerging Decision Support Systems in applications that include drought monitoring, reservoir management, and irrigation planning. The end-users such as RCMRD, NBI, Ethiopian and Kenya Meteorological and Famine Early Warning System Network (FEWSNet) will be the eventual benefactors of this work. There will be a capacity building process involving the above end-user organizations and transfer the models and the results for these organizations to execute for future use. The team has already initiated this study and the early results of first years' work are shown. The plan is to complete this work by late 2013.

Habib, Shahid↗
NASA NTRS1999

The Upper Atmosphere Research Satellite: From Coffee Table Art to Quantitative Science

The Upper Atmosphere Research Satellite (UARS) has provided an unprecedented set of observations of constituents of the stratosphere. When used in combination with data from other sources and appropriate modeling tools, these observations are useful for quantitative evaluation of stratospheric photochemical processes. This is illustrated by comparing ozone observations from airborne Differential Absorption Lidar (DIAL), from the Polar Ozone and Aerosol Measurement (POAM), from the Microwave Limb Sounder (MLS), and from the Halogen occultation Experiment (HALOE) with ozone fields generated with a three dimensional model. For 1995-96, at polar latitudes, observations from DIAL flights on December 9 and January 30, and POAM and MLS between late December and late January are compared with ozone fields from the GSFC 3D chemistry and transport model. Data from the three platforms consistently show that the observed ozone has a negative trend relative to the modeled ozone, and that the trend is uniform in time between early and mid winter, with no obvious dependence on proximity to the vortex edge. The importance of chlorine catalyzed photochemistry to this ozone loss is explored by comparing observations from MLS and HALOE with simulations for other northern winters, particularly 1997-98.

Douglass, Anne R.↗
NASA NTRS2014

Use of Semantic Technology to Create Curated Data Albums

One of the continuing challenges in any Earth science investigation is the discovery and access of useful science content from the increasingly large volumes of Earth science data and related information available online. Current Earth science data systems are designed with the assumption that researchers access data primarily by instrument or geophysical parameter. Those who know exactly the data sets they need can obtain the specific files using these systems. However, in cases where researchers are interested in studying an event of research interest, they must manually assemble a variety of relevant data sets by searching the different distributed data systems. Consequently, there is a need to design and build specialized search and discovery tools in Earth science that can filter through large volumes of distributed online data and information and only aggregate the relevant resources needed to support climatology and case studies. This paper presents a specialized search and discovery tool that automatically creates curated Data Albums. The tool was designed to enable key elements of the search process such as dynamic interaction and sense-making. The tool supports dynamic interaction via different modes of interactivity and visual presentation of information. The compilation of information and data into a Data Album is analogous to a shoebox within the sense-making framework. This tool automates most of the tedious information/data gathering tasks for researchers. Data curation by the tool is achieved via an ontology-based, relevancy ranking algorithm that filters out non-relevant information and data. The curation enables better search results as compared to the simple keyword searches provided by existing data systems in Earth science.

Ramachandran, Rahul↗
NASA NTRS1991

Image retrieval and processing system version 2.0 development work

The Image Retrieval and Processing System (IRPS) is a software package developed at Washington University and used by the NASA Regional Planetary Image Facilities (RPIF's). The IRPS combines data base management and image processing components to allow the user to examine catalogs of image data, locate the data of interest, and perform radiometric and geometric calibration of the data in preparation for analysis. Version 1.0 of IRPS was completed in Aug. 1989 and was installed at several IRPS's. Other RPIF's use remote logins via NASA Science Internet to access IRPS at Washington University. Work was begun on designing and population a catalog of Magellan image products that will be part of IRPS Version 2.0, planned for release by the end of calendar year 1991. With this catalog, a user will be able to search by orbit and by location for Magellan Basic Image Data Records (BIDR's), Mosaicked Image Data Records (MIDR's), and Altimetry-Radiometry Composite Data Records (ARCDR's). The catalog will include the Magellan CD-ROM volume, director, and file name for each data product. The image processing component of IRPS is based on the Planetary Image Cartography Software (PICS) developed by the U.S. Geological Survey, Flagstaff, Arizona. To augment PICS capabilities, a set of image processing programs were developed that are compatible with PICS-format images. This software includes general-purpose functions that PICS does not have, analysis and utility programs for specific data sets, and programs from other sources that were modified to work with PICS images. Some of the software will be integrated into the Version 2.0 release of IRPS. A table is presented that lists the programs with a brief functional description of each.

Slavney, Susan H.↗
NASA NTRS1977

Mariner Venus Mercury 1973 S/X-band experiment

The S/X-band experiment on the Mariner Venus/Mercury 1973 spacecraft constituted a unique opportunity to demonstrate the capability of an X-band downlink coherent with the normal S-band downlink. This was both a technological and scientific experiment, and the results indicated that it was successful in both cases. Analysis of the tracking data shows that the new S/X data type was capable of reducing the miss distance at the planet Mercury by 80% (post-processed data). The use of S/X electron content was demonstrated by comparison with Faraday rotation data. An X-band turnaround telemetry experiment showed the feasibility of a planetary X-band link. In the science area, the model atmospheric environment of Venus was refined. The ionosphere of the planet was measured to a higher accuracy than before, and the value of the dual-frequency link for measuring the scale size of turbulence was demonstrated. The estimate of the scale size was increased from 100 m to above 5 km.

Levy, G. S.↗
NASA NTRS1979

Proposed methods for the reconstruction of the Pioneer/Venus probe entry trajectories

In connection with the Pioneer Venus Project, an orbiter and an array of atmospheric probes are sent to Venus in separate launches during 1978. The four probes, which are transported to the planet on an instrumented Bus are released approximately 20 days prior to encounters. There are three identical small probes and a large probe. Each is designed to make in-situ atmospheric measurements. One of the principal scientific objectives of the Pioneer Venus (P/V) multiprobe mission is the determination of the structure and composition of the Venusian atmosphere down to the planet surface. To enhance the science return it is of paramount importance to be able to accurately determine the spacecraft entry trajectories. In addition to the in-situ spacecraft measurements, earth-based Doppler data are available. The process felt to be most applicable for the P/V multiprobe entry trajectory reconstruction is considered, with emphasis placed on the highly dynamic upper entry segment of the trajectory.

Findlay, J. T.↗
NASA NTRS1991

Advanced computing

Advanced concepts in hardware, software and algorithms are being pursued for application in next generation space computers and for ground based analysis of space data. The research program focuses on massively parallel computation and neural networks, as well as optical processing and optical networking which are discussed under photonics. Also included are theoretical programs in neural and nonlinear science, and device development for magnetic and ferroelectric memories.

Source record↗
NASA NTRS1999

The Utility and Validity of Kinematic GPS Positioning for the Geosar Airborne Terrain Mapping Radar System

GeoSAR is an airborne, interferometric Synthetic Aperture Radar (IFSAR) system for terrain mapping, currently under development by a consortium including NASA's Jet Propulsion Laboratory (JPL), Calgis, Inc., a California mapping sciences company, and the California Department of Conservation (CaIDOC), with funding provided by the U.S. Army Corps of Engineers Topographic Engineering Center (TEC) and the U.S. Defense Advanced Research Projects Agency (DARPA). IFSAR data processing requires high-accuracy platform position and attitude knowledge. On 9 GeoSAR, these are provided by one or two Honeywell Embedded GPS Inertial Navigation Units (EGI) and an Ashtech Z12 GPS receiver. The EGIs provide real-time high-accuracy attitude and moderate-accuracy position data, while the Ashtech data, post-processed differentially with data from a nearby ground station using Ashtech PNAV software, provide high-accuracy differential GPS positions. These data are optimally combined using a Kalman filter within the GeoSAR motion measurement software, and the resultant position and orientation information are used to process the dual frequency (X-band and P-band) radar data to generate high-accuracy, high -resolution terrain imagery and digital elevation models (DEMs). GeoSAR requirements specify sub-meter level planimetric and vertical accuracies for the resultant DEMS. To achieve this, platform positioning errors well below one meter are needed. The goal of GeoSAR is to obtain 25 cm or better 3-D positions from the GPS systems on board the aircraft. By imaging a set of known point target corner-cube reflectors, the GeoSAR system can be calibrated. This calibration process yields the true position of the aircraft with an uncertainty of 20- 50 cm. This process thus allows an independent assessment of the accuracy of our GPS-based positioning systems. We will present an overview of the GeoSAR motion measurement system, focusing on the use of GPS and the blending of position data from the various systems. We will present the results of our calibration studies that relate to the accuracy the GPS positioning. We will discuss the effects these positioning, errors have on the resultant DEM products and imagery.

Freedman, Adam↗