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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.

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At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
NASA NTRS1988

Autonomous image data reduction by analysis and interpretation

Image data is a critical component of the scientific information acquired by space missions. Compression of image data is required due to the limited bandwidth of the data transmission channel and limited memory space on the acquisition vehicle. This need becomes more pressing when dealing with multispectral data where each pixel may comprise 300 or more bytes. An autonomous, real time, on-board image analysis system for an exploratory vehicle such as a Mars Rover is developed. The completed system will be capable of interpreting image data to produce reduced representations of the image, and of making decisions regarding the importance of data based on current scientific goals. Data from multiple sources, including stereo images, color images, and multispectral data, are fused into single image representations. Analysis techniques emphasize artificial neural networks. Clusters are described by their outlines and class values. These analysis and compression techniques are coupled with decision making capacity for determining importance of each image region. Areas determined to be noise or uninteresting can be discarded in favor of more important areas. Thus limited resources for data storage and transmission are allocated to the most significant images.

Eberlein, Susan↗
NASA NTRS1988

Autonomous image data reduction by analysis and interpretation

Image data is a critical component of the scientific information acquired by space missions. Compression of image data is required due to the limited bandwidth of the data transmission channel and limited memory space on the acquisition vehicle. This need becomes more pressing when dealing with multispectral data where each pixel may comprise 300 or more bytes. An autonomous, real time, on-board image analysis system for an exploratory vehicle such as a Mars Rover is developed. The completed system will be capable of interpreting image data to produce reduced representations of the image, and of making decisions regarding the importance of data based on current scientific goals. Data from multiple sources, including stereo images, color images, and multispectral data, are fused into single image representations. Analysis techniques emphasize artificial neural networks. Clusters are described by their outlines and class values. These analysis and compression techniques are coupled with decision-making capacity for determining importance of each image region. Areas determined to be noise or uninteresting can be discarded in favor of more important areas. Thus limited resources for data storage and transmission are allocated to the most significant images.

Eberlein, Susan↗
NASA NTRS2001

Gridded Hourly Text Products: A TRMM Data Reduction Approach

The quantity of precipitation data from satellite-based observations is a blessing and a curse. The sheer volume of the data makes it difficult for many researchers to use in targeted applications. This volume increases further as algorithm improvements lead to the reprocessing of mission data. In addition to the overall volume of data, the size and format complexity of orbital granules contribute to the difficulty in using all the available data. Finally, the number of different instruments available to measure rainfall and related parameters further contributes to the volume concerns. In summary, we have an embarrassment of riches. The science team of the Tropical Rainfall Measuring Mission (TRMM) recognized this dilemma and has developed a strategy to address it. The TRMM Science Data and Information System (TSDIS) produces, at the direction of the Joint TRMM Science Team, a number of instantaneous rainfall products. The TRMM Microwave Imager (TMI), the Precipitation Radar and a Combined TMI/PR are the key "instruments" used in this production. Each of these products contains an entire orbit of data. The algorithm code computes not just rain rates but a large number of other physical parameters as well as information needed for monitoring algorithm performance. That makes these products very large. For example, a single orbit of TMI rain rate product is 99 MB, a single orbit of the combined product yields a granule that is 158 MB, while the 80 vertical levels of rain information from the PR yields an orbital product of 253 MB. These are large products that are often difficult for science users to electronically transfer to their sites especially if they want a large period of time. Level 3 gridded products are much smaller, but their 5 or 30 day temporal resolution is insufficient for many researchers. In addition, TRMM standard products are produced in the HDF format. While a large number of user-friendly tools are available to hide the details of the format (including a toolkit developed at TSDIS for the TRMM science team), many potential users shy away

Stocker, Erich↗
NASA NTRS2002

Spectral Data Reduction via Wavelet Decomposition

The greatest advantage gained from hyperspectral imagery is that narrow spectral features can be used to give more information about materials than was previously possible with broad-band multispectral imagery. For many applications, the new larger data volumes from such hyperspectral sensors, however, present a challenge for traditional processing techniques. For example, the actual identification of each ground surface pixel by its corresponding reflecting spectral signature is still one of the most difficult challenges in the exploitation of this advanced technology, because of the immense volume of data collected. Therefore, conventional classification methods require a preprocessing step of dimension reduction to conquer the so-called "curse of dimensionality." Spectral data reduction using wavelet decomposition could be useful, as it does not only reduce the data volume, but also preserves the distinctions between spectral signatures. This characteristic is related to the intrinsic property of wavelet transforms that preserves high- and low-frequency features during the signal decomposition, therefore preserving peaks and valleys found in typical spectra. When comparing to the most widespread dimension reduction technique, the Principal Component Analysis (PCA), and looking at the same level of compression rate, we show that Wavelet Reduction yields better classification accuracy, for hyperspectral data processed with a conventional supervised classification such as a maximum likelihood method.

Kaewpijit, S.↗
NASA NTRS2004

GRACE KBR and Accelerometer Data Reduction and Calibration

The Gravity Recovery and Climate Experiment (GRACE), launched on March 17, 2002, represents the state-of-the-art in geodetic observations of the static and time varying components of the Earth's geopotential field. The fundamental measurement used to observe gravity is the inter-satellite range and range rate between two coplanar, low altitude satellites obtained from a K-band ranging (KBR) system. In addition to the K-band ranging system, each satellite possess a Super-STAR Accelerometer, a GPS receiver/antenna package, Star Cameras and a Laser Retro Reflector (LRR) to complete the compliment of science instruments. The GRACE project has now released two years of Level 1B data derived from the science instruments and sensors. An integral component of our time variable gravity research is the reduction, calibration and analyses of these Level 1B data. In particular we have analyzed several months of K-band ranging (KBR1B), accelerometry (ACC1B) and GPS navigation (GNAV1B) data. Accelerometer calibration and KBR data reduction methodology and results will be presented. We discuss the impact of these analyses on the recovery of time variable gravity.

Rowlands, David D.↗
NASA NTRS1984

Ongoing data reduction, theoretical studies and supporting research in magnetospheric physics

Data from ISEE-3, Pioneer Venus Orbiter, and Voyager 1 and 2 were analyzed. The predictability of local shock macrostructure at ISEE-1, at the Earth's bow shock, from solar wind measurements made up-stream by ISEE-3, was conducted using computer graphic format. Morphology of quasi-parallel shock was reviewed. The review attempted to interrelate various measurements and computations involving the q-parallel structure and foreshock elements connected to it. A new classification for q-parallel morphology was suggested.

Scarf, F. L.↗
NASA NTRS1994

(abstract) Venus Gravity Data Reduction

The Magellan spacecraft has provided high resolution gravity data to its very end, October 13, 1994, when it was consumed by the Venusian atmosphere. After aerobraking in August of 1993 to attain a near circular orbit, excellent high latitude data were acquired which previously were very weak during the elliptical orbit coverage. There are 1500 orbits during the near circular orbit, supplying redundant coverage at different geometries over many features. This allowed the relaxation of apriori constraints, so true amplitudes are being extracted from the data. In this paper we present the results of a 75(sup th) degree and order field that incorporates all the old Pioneer Venus Orbiter data as well as all the Magellan data to September 1994. The new results reflect even higher correlation with topography, higher amplitude values for the highs and lows, and global results that have essentially very little apriori constraint on the solution parameters. We also correlate our new model with the earlier ones based on 60(sup th) and 40(sup th) degree and order presentations.

Magellan Venus gravity orbits topography surface f↗
NASA NTRS2003

Vector-Ordering Filter Procedure for Data Reduction

The vector-ordering filter (VOF) technique involves a procedure for sampling a large population of data vectors to select a subset of data vectors that fully characterize the state space of the large population. The VOF technique enables a large reduction of the volume of data that must be handled in the automated monitoring system and method discussed in the two immediately preceding articles. In so doing, the VOF technique enables the development of data-driven mathematical models of a monitored asset from sets of data that would otherwise exceed the memory capacities of conventional engineering computers. Data-driven mathematical models have been shown to offer high fidelity for purposes of control and monitoring of assets. In practice, a collection of asset-operating observations is acquired with the intention that the collection contain observations characteristic of the full dynamic range of operation of the asset. Often, such a collection contains an extremely large number of observations, many of which are redundant. The VOF technique fills the need for a means to extract, from the original collection of observational data, a reduced data matrix that excludes redundant data while maintaining the full statistical character and dynamic range of the original data. The reduced data matrix can then be used as the input data for development of a mathematical model of the monitored asset, or as training data for a neural-network substitute for an explicit mathematical model of the asset. Alternatively, the reduced data matrix can, itself, be used directly as a mathematical model of the monitored asset, as is commonly done in multivariate state-estimation techniques. The original data are collected from the asset over a range of operating states and are put in matrix form. Each column vector in the original data matrix represents the signal values acquired at a particular operational state of the asset. Thus, the number of columns of the original data matrix equals the number of observed states and the number of rows in this matrix equals the number of signals acquired at each observation. In the VOF technique, one extracts the reduced data matrix from the original data matrix through the selection of a representative subset of the column (state) vectors.

Bickford, Randall L.↗
NASA NTRS1990

Planetary astronomy of Mars. Mars data reduction

Grant #NAGW-1408 was specifically awarded to obtain telescopic visible and near-IR spectral imaging of Mars during the 1988 apparition (9/28/88). The observing program was highly successful producing approximately 2 Gbytes of data, but was only funded for one year and virtually all of the funds were spent in data acquisition. The follow-up grant was funded the following year for reduction of these data into a scientifically productive form, which because of the size and nature of our observations, was a non-trivial task. A more detailed scientific analysis of these data (fully reduced) is in progress now and will take a number of years. Extended geologic analyses of the astronomical data are being funded by the NASA Planetary Geology and Geophysics program. The objective was to produce detailed reflectance spectra for contiguous, spatially resolved surface elements covering most of the planet (about +50 degrees to -90 degrees latitude, all longitudes). A total of 6 observing runs, of 3-4 days duration each, were conducted on the University of Arizona's 1.5m telescope on Mt. Bigelow. We present a sketch map showing the approximate total extent of our spectral image coverage. Nearly all of Mars south of 40 degrees N was observed at least once. About half of the area shown was observed multiple times. South of 65 degrees S, including the south polar cap, our coverage is heavily redundant. The first run was conducted June 29 - July 1, 1988 (all dates are UT) to serve as a baseline prior to possible dust storm activity on Mars. The other observing runs were closer to opposition: Sept. 3-6, 13-15, 24-26, and Oct. 5-7 and 16-18. The September and October observations were scheduled to provide maximum longitudinal coverage. This was also intended to provide a balance between surface observations and observations of predicted dust storm activity. No global dust storm developed in 1988, so we have a large volume of data for the surface of Mars.

Singer, Robert B.↗
NASA NTRS1973

Conversational high resolution mass spectrographic data reduction

A FORTRAN 4 program is described which reduces the data obtained from a high resolution mass spectrograph. The program (1) calculates an accurate mass for each line on the photoplate, and (2) assigns elemental compositions to each accurate mass. The program is intended for use in a time-shared computing environment and makes use of the conversational aspects of time-sharing operating systems.

Romiez, M. P.↗
NASA NTRS1980

Data reduction by computer processing

The automated analysis of remote sensing data, specifically digital processing of LANDSAT or other image data in numerical form was considered in a technical workshop which covered the teaching of digital image processing, including both theoretical and applied subjects and laboratory experience, and also reviewed NASA developed image processing software, and hardware/software systems employed at NASA-Ames Research Center in support of the Western Regional Applications Program (WRAP). A course titled Image Processing Lab, one of two courses required for a graduate minor in remote sensing at Arizona is examined as well as the rationale, content, and hardware/software support for this course.

Lumb, D. R.↗
NASA NTRS1993

Residual acceleration data on IML-1: Development of a data reduction and dissemination plan

The research performed consisted of three stages: (1) identification of sensitive IML-1 experiments and sensitivity ranges by order of magnitude estimates, numerical modeling, and investigator input; (2) research and development towards reduction, supplementation, and dissemination of residual acceleration data; and (3) implementation of the plan on existing acceleration databases.

Rogers, Melissa J. B.↗
NASA NTRS1995

User's manual for the one-dimensional hypersonic experimental aero-thermodynamic (1DHEAT) data reduction code

A FORTRAN computer code for the reduction and analysis of experimental heat transfer data has been developed. This code can be utilized to determine heat transfer rates from surface temperature measurements made using either thin-film resistance gages or coaxial surface thermocouples. Both an analytical and a numerical finite-volume heat transfer model are implemented in this code. The analytical solution is based on a one-dimensional, semi-infinite wall thickness model with the approximation of constant substrate thermal properties, which is empirically corrected for the effects of variable thermal properties. The finite-volume solution is based on a one-dimensional, implicit discretization. The finite-volume model directly incorporates the effects of variable substrate thermal properties and does not require the semi-finite wall thickness approximation used in the analytical model. This model also includes the option of a multiple-layer substrate. Fast, accurate results can be obtained using either method. This code has been used to reduce several sets of aerodynamic heating data, of which samples are included in this report.

Hollis, Brian R.↗
NASA NTRS1976

A combined boundary-profile and automated data-reduction and analysis system

A portable boundary-layer meteorological data-acquisition and analysis system is described which employs a small tethered balloon and a programmable calculator. The system is capable of measuring pressure, wet- and dry-bulb temperature, wind speed, and temperature fluctuations as a function of height and time. Other quantities, which can be calculated in terms of these, can also be made available in real time. All quantities, measured and calculated, can be printed, plotted, and stored on magnetic tape in the field during the data-acquisition phase of an experiment.

Deloach, R.↗
NASA NTRS1995

Galileo Heat Shield Response Experiment Data Reduction and Analyses

The Galileo heat shield response experiment consists of 10 Analog Resistance Ablation Detectors (ARADs) embedded in the carbon phenolic heat shield. As the vehicle descends into the atmosphere of Jupiter, these ARADs will in effect measure the recession as a function of time at various locations on the heat shield. This recession data will be used to reconstruct the time-dependent shape of the vehicle. The shape data is of critical importance to the Atmospheric Reconstruction Experiment which must know mass and drag coefficient of the vehicle in order to determine the structure of the Jovian atmosphere. The data is also intrinsically useful as a database for evaluating the accuracy of our numerical codes and methodology for predicting highly radiating reentry flowfields and coupled heat shield material response. This paper will document the reduction of the data from the ARAD sensors, reconstruction of the heat shield shape history, and comparison of the actual heat shield response with previous calculations and experiments. If possible, we will also include results from new calculations which couple the shock layer flow with the transient material response.

Milos, Frank S.↗