SEARCH · Search NASA

Results for “data processing”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,135 records · Page 63

All sources NASA NTRS DOE OSTI

NASA NTRSDate not supplied

An Autonomous sUAS Operating in UTM TCL4+ and STEReO Fire Scenario

This study presents a sUAS payload point design that enables autonomous BVLOS flightin UTM TCL4+ urban environments and STEReO fire responses. The payload components include an onboard computer, 360 deg LIDAR, range finder altimeter, downward-facing monocular camera, forward-facing thermal and visible light dual camera, vehicle-to-vehicle radio modem, and Li-ion smart battery. The components are mounted on an enclosed structural frame that was designed in-house. Placing the autonomy components onboard leverages the advantages of sUAS over manned aircraft such as low-cost, quick response time, and increased scalability. Autonomous capabilities include object and fire detection, V2V communication, embedded processing, and SLAM. Data processing is conducted on-board the aircraft to eliminate the dependency on a ground station downlink. The payload is evaluated in both software simulation as well as flight tests.

Autonomous UAS↗

NASA NTRSDate not supplied

An Oveview of TROPESS Data Products and Services at the NASA GES DISC

The TRopospheric Ozone and Precursors from Earth System Sounding (TROPESS) project generates Earth System Data Records (ESDRs) of ozone, and other atmospheric constituents (CH4,CO, H2O, HDO, NH3, PAN and temperature) by processing data from multiple satellites through a common retrieval algorithm and ground data system. Satellite Level-1B input data used in generating the TROPESS L2 data products include CrIS NOAA-20 (JPSS-1), CrIS SNPP, AIRS Aqua, OMI Aura, and TROPOMI S5P. The common retrieval framework is known as the MUlti-SpEctra, MUlti-SpEcies, Multi-SEnsors (MUSES) science data processing system (MUSES-SDPS). Several of the TROPESS data products are now available from the NASA Goddard Earth Sciences Data and Information Service Center (GES DISC) for users to download. In this presentation we provide an overview of the various TROPESS data products. These data products can be divided into the following Forward Stream types: Standard Products, Summary Products, and Full-Archival Products. Standard Products are for users that are doing full analysis with avenging kernel and covariance corresponding to retrieved vertical profiles. Summary products have a smaller file size and are more convenient for first-look and rapid analysis, include total and partial columns, as well as column averaging kernels. The Full-Archival Products will contain all information used in creating the data. TROPESS also creates Special Products, provided on an as-needed and as-available basis to support NASA field missions and individual-investigator requests over specific regions. Eventually, TROPESS will also produce and deliver a set of Reanalysis Stream products. Data at the GES DISC are being transitioned into the "Cloud". This will allow users with "Cloud” access to perform data analysis directly on the data without downloading the data to their system. Services, such as subsetting and data visualization, will also be provided for TROPESS data products at the GES DISC.

James Johnson↗

NASA NTRS2024

The Radio Fundamental Catalogue. I. Astrometry

We present the all-sky catalogue of absolute positions and estimates of correlated flux density of 21,942 compact radio sources determined from processing interferometric visibility data of virtually all VLBI observing sessions at 2 to 23~GHz from 72 programs suitable for absolute astrometry collected for 30 years. We used a novel technique of generation of a dataset of fused observables that allowed us to incorporate all available data in our analysis. The catalogue is the most complete and most precise to date. It forms the foundation and reference for positional astronomy, space geodesy, space navigation, population analysis of active galactic nuclei (AGNs), and provides calibrators for phase-referencing for differential astrometry and VLBI astrophysical observations. Its accuracy was evaluated through a detailed accounting systematic errors, rigorous decimation tests, comparison of different datasets, and comparison with other catalogues. The catalogue samples preferentially the AGNs with a strong contemporary parsec-scale synchrotron emission. Its milliarcsecond level positional accuracy allows association of these AGNs with detections in a wide range of the electromagnetic spectrum from low-frequency radio to gamma-rays and high energy neutrinos. We describe the innovative data processing and calibration technique in full detail, report the in depth analysis of random and systematic positional errors, and provide the list of associations with large surveys at different wavelengths.

Astronomy↗

NASA NTRS2007

Production and Distribution of NASA MODIS Remote Sensing Products

The two Moderate Resolution Imaging Spectroradiometer (MODIS) instruments on-board NASA's Earth Observing System (EOS) Terra and Aqua satellites make key measurements for understanding the Earth's terrestrial ecosystems. Global time-series of terrestrial geophysical parameters have been produced from MODIS/Terra for over 7 years and for MODIS/Aqua for more than 4 1/2 years. These well calibrated instruments, a team of scientists and a large data production, archive and distribution systems have allowed for the development of a new suite of high quality product variables at spatial resolutions as fine as 250m in support of global change research and natural resource applications. This talk describes the MODIS Science team's products, with a focus on the terrestrial (land) products, the data processing approach and the process for monitoring and improving the product quality. The original MODIS science team was formed in 1989. The team's primary role is the development and implementation of the geophysical algorithms. In addition, the team provided feedback on the design and pre-launch testing of the instrument and helped guide the development of the data processing system. The key challenges the science team dealt with before launch were the development of algorithms for a new instrument and provide guidance of the large and complex multi-discipline processing system. Land, Ocean and Atmosphere discipline teams drove the processing system requirements, particularly in the area of the processing loads and volumes needed to daily produce geophysical maps of the Earth at resolutions as fine as 250 m. The processing system had to handle a large number of data products, large data volumes and processing loads, and complex processing requirements. Prior to MODIS, daily global maps from heritage instruments, such as Advanced Very High Resolution Radiometer (AVHRR), were not produced at resolutions finer than 5 km. The processing solution evolved into a combination of processing the lower level (Level 1) products and the higher level discipline specific Land and Atmosphere products in the MODIS Science Investigator Lead Processing System (SIPS), the MODIS Adaptive Processing System (MODAPS), and archive and distribution of the Land products to the user community by two of NASA s EOS Distributed Active Archive Centers (DAACs). Recently, a part of MODAPS, the Level 1 and Atmosphere Archive and Distribution System (LAADS), took over the role of archiving and distributing the Level 1 and Atmosphere products to the user community.

Wolfe, Robert↗

NASA NTRS1975

Remote terminal system evaluation

An Earth Resources Data Processing System was developed to evaluate the system for training, technology transfer, and data processing. In addition to the five sites included in this project two other sites were connected to the system under separate agreements. The experience of these two sites is discussed. The results of the remote terminal project are documented in seven reports: one from each of the five project sites, Purdue University, and an overview report summarizing the other six reports.

Phillips, T. L.↗

NASA NTRS1978

Remote sensing of Gulf Stream using GEOS-3 radar altimeter

Radar altimeter measurements from the GEOS-3 satellite to the ocean surface indicated the presence of expected geostrophic height differences across the the Gulf Stream. Dynamic sea surface heights were found by both editing and filtering the raw sea surface heights and then referencing these processed data to a 5 minute x 5 minute geoid. Any trend between the processed data and the geoid was removed by subtracting out a linear fit to the residuals in the open ocean. The mean current velocity of 107 + or - 29 cm/sec calculated from the dynamic heights for all orbits corresponded with velocities obtained from hydrographic methods. Also, dynamic topographic maps were produced for August, September, and October 1975. Results pointed out limitations in the accuracy of the geoid, height anomaly deteriorations due to filtering, and lack of dense time and space distribution of measurements.

Leitao, C. D.↗

NASA NTRS1984

A modeling analysis program for the JPL table mountain Io sodium cloud data

A detailed review of 110 of the 263 Region B/C images of the 1981 data set is undertaken and a preliminary assessment of 39 images of the 1976-79 data set is presented. The basic spatial characteristics of these images are discussed. Modeling analysis of these images after further data processing will provide useful information about Io and the planetary magnetosphere. Plans for data processing and modeling analysis are outlined. Results of very preliminary modeling activities are presented.

Smyth, W. H.↗

NASA NTRS2007

A Comprehensive Plan for the Long-Term Calibration and Validation of Oceanic Biogeochemical Satellite Data

The primary objective of this planning document is to establish a long-term capability and validating oceanic biogeochemical satellite data. It is a pragmatic solution to a practical problem based primarily o the lessons learned from prior satellite missions. All of the plan's elements are seen to be interdependent, so a horizontal organizational scheme is anticipated wherein the overall leadership comes from the NASA Ocean Biology and Biogeochemistry (OBB) Program Manager and the entire enterprise is split into two components of equal sature: calibration and validation plus satellite data processing. The detailed elements of the activity are based on the basic tasks of the two main components plus the current objectives of the Carbon Cycle and Ecosystems Roadmap. The former is distinguished by an internal core set of responsibilities and the latter is facilitated through an external connecting-core ring of competed or contracted activities. The core elements for the calibration and validation component include a) publish protocols and performance metrics; b) verify uncertainty budgets; c) manage the development and evaluation of instrumentation; and d) coordinate international partnerships. The core elements for the satellite data processing component are e) process and reprocess multisensor data; f) acquire, distribute, and archive data products; and g) implement new data products. Both components have shared responsibilities for initializing and temporally monitoring satellite calibration. Connecting-core elements include (but are not restricted to) atmospheric correction and characterization, standards and traceability, instrument and analysis round robins, field campaigns and vicarious calibration sites, in situ database, bio-optical algorithm (and product) validation, satellite characterization and vicarious calibration, and image processing software. The plan also includes an accountability process, creating a Calibration and Validation Team (to help manage the activity), and a discussion of issues associated with the plan's scientific focus.

Hooker, Stanford B.↗

NASA NTRS1978

Large-scale Gulf Stream frontal study using GEOS 3 radar altimeter data

From data obtained by the GEOS 3 radar altimeter, sea surface heights are found by both editing and filtering the raw sea surface height measurements and then referencing these processed data to a 5 foot by 5 foot geoid. Any trend between the processed data and the geoid is removed by subtracting out a linear fit to the residuals in the open ocean. Data from individual passes are further processed by applying a minimum variance technique at the subsatellite crossing points to produce surface topography maps for the 6 months and an overall mean map which reveal important details about the Gulf Stream system. The differences between the monthly mean and the overall mean are calculated for each of the 6 months to show the temporal and spatial changes of the Gulf Stream front and spawned eddies. The standard deviation map is even more informative and shows preferred locations of Gulf Stream meanders.

Huang, N. E.↗

NASA NTRS2016

Description of the TCERT Vetting Reports for Data Release 25

This document, the Kepler Instrument Handbook (KIH), is for Kepler and K2 observers, which includes the Kepler Science Team, Guest Observers (GOs), and astronomers doing archival research on Kepler and K2 data in NASAs Astrophysics Data Analysis Program (ADAP). The KIH provides information about the design, performance, and operational constraints of the Kepler flight hardware and software, and an overview of the pixel data sets available. The KIH is meant to be read with these companion documents:1. Kepler Data Processing Handbook (KSCI-19081) or KDPH (Jenkins et al., 2016). The KDPH describes how pixels downlinked from the spacecraft are converted by the Kepler Data Processing Pipeline (henceforth just the pipeline) into the data products delivered to the MAST archive. 2. Kepler Archive Manual (KDMC-10008) or KAM (Thompson et al., 2016). The KAM describes the format and content of the data products, and how to search for them.3. Kepler Data Characteristics Handbook (KSCI-19040) or KDCH (Christiansen et al., 2016). The KDCH describes recurring non-astrophysical features of the Kepler data due to instrument signatures, spacecraft events, or solar activity, and explains how these characteristics are handled by the pipeline.4. Kepler Data Release Notes 25 (KSCI-19065) or DRN 25 (Thompson et al., 2015). DRN 25 describes signatures and events peculiar to individual quarters, and the pipeline software changes between a data release and the one preceding it.Together, these documents supply the information necessary for obtaining and understanding Kepler results, given the real properties of the hardware and the data analysis methods used, and for an independent evaluation of the methods used if so desired.

Instrument↗

NASA NTRS1979

Satellite pattern classification using charge transfer devices

The potential uses of Charge Transfer Devices (CTDs) in pattern classification operations are explored. The needs for a hardware-based pattern classifier are established, and a matrix multiplication subsystem based upon a sum-of-products CTD is presented. Applications of the subsystem to the classification of multi-modal Gaussian distributions in general and to LANDSAT data processing in particular are discussed. Finally, the potential impact of this technology on satellite data processing methodologies is discussed.

Snyder, W. E.↗

NASA NTRS1991

Goldstone solar system radar

This task provides for the planning, experiment design, and coordination of the data acquisition and engineering activities in support of all Goldstone planetary radar astronomy. Activities related to up-grades of the receiver systems, transmitter systems, and data processing support systems are currently intense. Also, the hardware and software maintenance of the data processing facility used by many of the Goldstone Solar System Radar investigators are covered.

Jurgens, Raymond F.↗

NASA NTRS2010

Distinguishing Provenance Equivalence of Earth Science Data

Reproducibility of scientific research relies on accurate and precise citation of data and the provenance of that data. Earth science data are often the result of applying complex data transformation and analysis workflows to vast quantities of data. Provenance information of data processing is used for a variety of purposes, including understanding the process and auditing as well as reproducibility. Certain provenance information is essential for producing scientifically equivalent data. Capturing and representing that provenance information and assigning identifiers suitable for precisely distinguishing data granules and datasets is needed for accurate comparisons. This paper discusses scientific equivalence and essential provenance for scientific reproducibility. We use the example of an operational earth science data processing system to illustrate the application of the technique of cascading digital signatures or hash chains to precisely identify sets of granules and as provenance equivalence identifiers to distinguish data made in an an equivalent manner.

Tilmes, Curt↗

NASA NTRSDate not supplied

Biomass Harmonization and SAR Analysis with the Multi-mission Algorithm and Analysis Platform (MAAP)

The Multi‐mission Algorithm and Analysis Platform (MAAP) is a collaborative effort between NASA and the European Space Agency (ESA) to support above ground biomass (AGB) research in an open science framework. MAAP brings together relevant data, algorithms, and computing capabilities in a common cloud environment to address the challenges of sharing and processing data from field, airborne and satellite measurements. MAAP was publicly released in October 2021, providing computing capabilities co-located with the data, a collaborative coding and analysis environment, and a set of interoperable tools and algorithms developed to support the estimation and visualization of data. MAAP has allowed scientists from both North America and Europe to collaborate on the generation and analysis/visualization of data derived from multiple, discipline-adjacent missions in an open, collaborative environment that has reached beyond traditional scientific investigation. MAAP has been used to support multiple scientific activities. To date, existing LiDAR data from multiple platforms has been calibrated with field measurements and combined for more comprehensive and accurate estimates of above ground biomass AGB; these LiDAR platforms include airborne (e.g. LVIS), the International Space Station (NASA’s Global Ecosystem Dynamics Investigation (GEDI), and satellites (e.g. ICESat-2). The current challenge is to effectively and seamlessly combine the aforementioned LiDAR-based data with new data sources such as P-band RADAR from ESA’s upcoming BIOMASS mission, existing ESA Sentinel-1 C-band SAR, and the 30 PB/yr of high cadence global coverage L-band SAR data from the upcoming NASA-ISRO SAR (NISAR) mission. Recent analysis using MAAP merged ICESat-2 and optical data (Harmonized Landsat Sentinel) produced the most comprehensively precise estimate of boreal-wide AGB to date. Another effort using MAAP is the production and open distribution of global comparisons of AGB map estimates, including from ICESat-2 and GEDI, to bolster stakeholder uptake for policy applications. These map estimates will feed into the Intergovernmental Panel on Climate Change (IPCC) database, likely aiding the next Global Carbon Stocktake of the UNFCCC. Furthermore, the biomass retrieval intercomparison exercise BRIX-2 could benefit from the MAAP providing standardized test cases (based on airborne campaign and spaceborne data) allowing the community to develop and apply retrieval algorithms based on these test cases, while forthcoming SAR data training curricula could also use the MAAP as a teaching and learning platform. The MAAP is meeting the challenges inherent in international, open science collaboration and large scale computing with a platform that is entirely open source and cloud native, using open standards for data access, manipulation, protocols, and formats. The MAAP data system consists of a dedicated data store whose data is indexed in an online catalog conforming to established metadata, application programmatic interfaces (APIs), and service interface standards, using an implementation of the open sourced NASA Common Metadata Repository. Federation of user identities allows users from either NASA or ESA to access and consume services from the other using a unified metadata catalog for the data utilized across the ESA and NASA MAAP platforms. Similarly, we are exploring how to increase interoperability to achieve a common approach to packaging, orchestrating and executing algorithms, with interoperable access to data for subsetting, fast browse, and cloud-optimized access, all using interoperable standards such as those from the Open Geospatial Consortium (OGC). Designed for interoperability, ESA and NASA utilize a common architecture for the software platform. It provides a cloud-based algorithm development environment (ADE) that enables scientists to develop algorithms collaboratively with access to the MAAP data catalog as well as other data archives. MAAP provides an Eclipse Che-based ADE supporting both Python and R languages, popular in this biomass community. Algorithms developed and containerized within the ADE can be deployed to run to thousands of computational nodes in the MAAP’s data processing system (DPS), dramatically speeding up processing and giving scientists a rapid, iterative turnaround of results. NASA’s implementation of the DPS is based on the Hybrid Science Data System (HySDS) framework, used by NASA flight projects to produce Earth science standard products.

cloud computing↗

NASA NTRS2011

High-Throughput, Adaptive FFT Architecture for FPGA-Based Spaceborne Data Processors

Exponential growth in microelectronics technology such as field-programmable gate arrays (FPGAs) has enabled high-performance spaceborne instruments with increasing onboard data processing capabilities. As a commonly used digital signal processing (DSP) building block, fast Fourier transform (FFT) has been of great interest in onboard data processing applications, which needs to strike a reasonable balance between high-performance (throughput, block size, etc.) and low resource usage (power, silicon footprint, etc.). It is also desirable to be designed so that a single design can be reused and adapted into instruments with different requirements. The Multi-Pass Wide Kernel FFT (MPWK-FFT) architecture was developed, in which the high-throughput benefits of the parallel FFT structure and the low resource usage of Singleton s single butterfly method is exploited. The result is a wide-kernel, multipass, adaptive FFT architecture. The 32K-point MPWK-FFT architecture includes 32 radix-2 butterflies, 64 FIFOs to store the real inputs, 64 FIFOs to store the imaginary inputs, complex twiddle factor storage, and FIFO logic to route the outputs to the correct FIFO. The inputs are stored in sequential fashion into the FIFOs, and the outputs of each butterfly are sequentially written first into the even FIFO, then the odd FIFO. Because of the order of the outputs written into the FIFOs, the depth of the even FIFOs, which are 768 each, are 1.5 times larger than the odd FIFOs, which are 512 each. The total memory needed for data storage, assuming that each sample is 36 bits, is 2.95 Mbits. The twiddle factors are stored in internal ROM inside the FPGA for fast access time. The total memory size to store the twiddle factors is 589.9Kbits. This FFT structure combines the benefits of high throughput from the parallel FFT kernels and low resource usage from the multi-pass FFT kernels with desired adaptability. Space instrument missions that need onboard FFT capabilities such as the proposed DESDynl, SWOT (Surface Water Ocean Topography), and Europa sounding radar missions would greatly benefit from this technology with significant reductions in non-recurring cost and risk.

NguyenKobayashi, Kayla↗

NASA NTRS1994

Analysis of plasma measurements for the Geotail mission

Data processing and research efforts for the period October 1993 to September 1994 are reported. Routine data processing includes the production of color spectrograms and computing of quantitative plasma parameters such as the plasma number density, bulk flow velocity, temperature, and pressure. In addition, specialized analysis software is being developed for specific and general applications. Research activities include the measurement of plasmas from the Geotail spacecraft; the processing of the measurements from a hot plasma analyzer to compute one minute averages of plasma densities, temperatures, and velocities for a substantial part of the Geotail deep tail mission; and, a preliminary survey of the magnetotail for geocentric radial distances of 10 to 210 earth radii. The topology of the magnetotail with its various regions and boundaries is determined by a complex interaction with the fields and plasmas of the solar wind. Observations of the rotation of the magnetic field in the solar wind show that it is well correlated with repeated transitions at Geotail from the magnetotail lobe to a magnetosheath-like boundary layer.

Frank, Louis A.↗

NASA NTRS2001

Lessons from Adaptive Level One Accelerator (ALOA) System Implementation

The Adaptive Level One Accelerator (ALOA) system was developed as part of the Earth Science Data and Information System (ESDIS) project. The reconfigurable computing technologies were investigated for Level 1 satellite telemetry data processing to achieve computing acceleration and cost reduction for the next-generation Level 1 data processing systems. The MODIS instrument calibration algorithm was implemented using reconfigurable a computer. The system development process and the lessons learned throughout the design cycle are summarized in this paper.

Patel, Umesh D.↗

NASA NTRS2007

Mars-Approach Navigation Using In Situ Orbiters

A document discusses the continuing development of a navigation system that would enable a spacecraft to approach Mars on a trajectory precise enough to enable the spacecraft to land within 1 km of a specified location on the Martian surface. This degree of accuracy would represent an order-of-magnitude improvement over that now obtained in radiometric tracking by use of the Deep Space Network. The navigation system would be implemented largely in software running in digital processors in the Electra transceiver, the Mars Network s standard radio transceiver, that would be in both the approaching spacecraft and Mars Network orbiter. The Mars Network is an ad hoc constellation of existing and future Mars science orbiters and dedicated telecommunication orbiters that has been established as a communication and navigation infrastructure to support the exploration of Mars. The software would exploit the sensory and data-processing capabilities of the Electra transceivers to gather Doppler-shift and other radiometric tracking data and process those data into trajectories data that would be accurate to within 0.3 km at the point of entry into the Martian atmosphere (as needed to land within 1 km of a target surface location).

Duncan, Courtney↗