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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
NASA NTRS2003

First Year Wilkinson Microwave Anisotropy Probe(WMAP) Observations: Data Processing Methods and Systematic Errors Limits

We describe the calibration and data processing methods used to generate full-sky maps of the cosmic microwave background (CMB) from the first year of Wilkinson Microwave Anisotropy Probe (WMAP) observations. Detailed limits on residual systematic errors are assigned based largely on analyses of the flight data supplemented, where necessary, with results from ground tests. The data are calibrated in flight using the dipole modulation of the CMB due to the observatory's motion around the Sun. This constitutes a full-beam calibration source. An iterative algorithm simultaneously fits the time-ordered data to obtain calibration parameters and pixelized sky map temperatures. The noise properties are determined by analyzing the time-ordered data with this sky signal estimate subtracted. Based on this, we apply a pre-whitening filter to the time-ordered data to remove a low level of l/f noise. We infer and correct for a small (approx. 1 %) transmission imbalance between the two sky inputs to each differential radiometer, and we subtract a small sidelobe correction from the 23 GHz (K band) map prior to further analysis. No other systematic error corrections are applied to the data. Calibration and baseline artifacts, including the response to environmental perturbations, are negligible. Systematic uncertainties are comparable to statistical uncertainties in the characterization of the beam response. Both are accounted for in the covariance matrix of the window function and are propagated to uncertainties in the final power spectrum. We characterize the combined upper limits to residual systematic uncertainties through the pixel covariance matrix.

Hinshaw, G.↗
NASA NTRS1995

Data processing of solar EUV instruments on the METEOR satellite

The Multiple Experiment Transporter into Earth Orbit and Return-Solar EUV Experiment (METEOR-SEE) project will take daily extreme ultraviolet (EUV) irradiance spectra starting in the summer of 1995. The METEOR-SEE package consists of an EUV grating spectrograph (EGS) and a cluster of 5 soft x-ray photometers (XP's). Both these instruments have flown previously on NASA sounding rockets. Because of the scope of the project, new data processing algorithms had to be developed for the SEE instruments onboard the METEOR satellite. An overview of the data flow describes how satellite data are collected and processed. Detailed descriptions of specific routines will show what data processing entails.

Brown, Hipook↗
NASA NTRS1969

Computer program developed for flowsheet calculations and process data reduction

Computer program PACER-65, is used for flowsheet calculations and easily adapted to process data reduction. Each unit, vessel, meter, and processing operation in the overall flowsheet is represented by a separate subroutine, which the program calls in the order required to complete an overall flowsheet calculation.

Alfredson, P. G.↗
NASA NTRS1972

Space vehicle-borne application of optical data processing

A model is considered for vehicle-borne parallel optical data processing which might be used as a key part of an advanced earth resources satellite mission. Some typical applications and the operation of the on-board processor are discussed.

Welch, J. D.↗
NASA NTRS1988

Expert system technology as a data processing tool

The expert system technology is focused on as a data processing tool. Several existing applications are analyzed. Their original definition as pure expert systems is contrasted with their current status as integrated systems. The architectural requirements needed to support such a heterogeneous environment are given.

Hennessy, John F.↗
NASA NTRS1994

TOGA/COARE AMMR 1992 data processing

The complete set of Tropical Ocean and Global Atmosphere (TOGA)/Coupled Ocean Atmosphere Response Experiment (COARE) flight data for the 91.65 GHz Airborne Meteorological Radiometer (AMMR92) contains data from nineteen flights: two test flights, four transit flights, and thirteen experimental flights. The data flight occurred between December 16, 1992 and February 28, 1993. Data collection from the AMMR92 during the first ten flights of TOGA/COARE was performed using the executable code TSK30041. These are IBM PC/XT programs used by the NASA Goddard Space Flight Center (GSFC). During one flight, inconsistencies were found during the operation of the AMMR92 using the GSFC data acquisition system. Consequently, the Georgia Tech (GT) data acquisition system was used during all successive TOGA/COARE flights. These inconsistencies were found during the data processing to affect the recorded data as well. Errors are caused by an insufficient pre- and post-calibration setting period for the splash-plate mechanism. The splash-plate operates asynchronusly with the data acquisition system (there is no position feedback to the GSFC or GT data system). This condition caused both the calibration and the post-calibration scene measurement to be corrupted on a randomly occurring basis when the GSFC system was used. This problem did not occur with the GT data acquisition system due to sufficient allowance for splash-plate settling. After TOGA/COARE it was determined that calibration of the instrument was a function of the scene brightness temperature. Therefore, the orientation error in the main antenna beam of the AMMR92 is hypothesized to be caused by misalignment of the internal 'splash-plate' responsible for directing the antenna beam toward the scene or toward the calibration loads. Misalignment of the splash-plate is responsible for 'scene feedthrough' during calibration. Laboratory investigation at Georgia Tech found that each polarization is affected differently by the splash-plate alignment error. This is likely to cause significant and unique errors in the absolute calibration of each channel.

Kunkee, D. B.↗
NASA NTRS1978

Theory on data processing and instrumentation

A selection of NASA Earth observations programs are reviewed, emphasizing hardware capabilities. Sampling theory, noise and detection considerations, and image evaluation are discussed for remote sensor imagery. Vision and perception are considered, leading to numerical image processing. The use of multispectral scanners and of multispectral data processing systems, including digital image processing, is depicted. Multispectral sensing and analysis in application with land use and geographical data systems are also covered.

Billingsley, F. C.↗
NASA NTRS1991

Sizing the science data processing requirements for EOS

The methodology used in the compilation and synthesis of baseline science requirements associated with the 30 + EOS (Earth Observing System) instruments and over 2,400 EOS data products (both output and required input) proposed by EOS investigators is discussed. A brief background on EOS and the EOS Data and Information System (EOSDIS) is presented, and the approach is outlined in terms of a multilayer model. The methodology used to compile, synthesize, and tabulate requirements within the model is described. The principal benefit of this approach is the reduction of effort needed to update the analysis and maintain the accuracy of the science data processing requirements in response to changes in EOS platforms, instruments, data products, processing center allocations, or other model input parameters. The spreadsheets used in the model provide a compact representation, thereby facilitating review and presentation of the information content.

Wharton, Stephen W.↗
NASA NTRS1965

Science data processing.

Processing technique for scientific data telemetered to Earth from Mariner IV Mars probe

MARINER IV SPACE PROBE↗
NASA NTRS2005

Methodology for the Elimination of Reflection and System Vibration Effects in Particle Image Velocimetry Data Processing

A methodology to eliminate model reflection and system vibration effects from post processed particle image velocimetry data is presented. Reflection and vibration lead to loss of data, and biased velocity calculations in PIV processing. A series of algorithms were developed to alleviate these problems. Reflections emanating from the model surface caused by the laser light sheet are removed from the PIV images by subtracting an image in which only the reflections are visible from all of the images within a data acquisition set. The result is a set of PIV images where only the seeded particles are apparent. Fiduciary marks painted on the surface of the test model were used as reference points in the images. By locating the centroids of these marks it was possible to shift all of the images to a common reference frame. This image alignment procedure as well as the subtraction of model reflection are performed in a first algorithm. Once the images have been shifted, they are compared with a background image that was recorded under no flow conditions. The second and third algorithms find the coordinates of fiduciary marks in the acquisition set images and the background image and calculate the displacement between these images. The final algorithm shifts all of the images so that fiduciary mark centroids lie in the same location as the background image centroids. This methodology effectively eliminated the effects of vibration so that unbiased data could be used for PIV processing. The PIV data used for this work was generated at the NASA Langley Research Center Quiet Flow Facility. The experiment entailed flow visualization near the flap side edge region of an airfoil model. Commercial PIV software was used for data acquisition and processing. In this paper, the experiment and the PIV acquisition of the data are described. The methodology used to develop the algorithms for reflection and system vibration removal is stated, and the implementation, testing and validation of these algorithms are presented.

Bremmer, David M.↗
NASA NTRS1972

Data processing requirements for the Earth Resources Technology Satellite (ERTS)

Some of the data handling considerations that led to the formulation of the data processing requirements for the ERTS system are discussed. The significant parameters that influence these requirements are: (1) payload characteristics, (2) spacecraft characteristics such as orbit, attitude and attitude rates, (3) payload coverage, and (4) product types and quantities. Items 3 and 4 have had the most significant influence on the generation of the requirements.

Sos, J. Y.↗
NASA NTRS1977

Remote sensing data processing: Two years ago, today, and two years from today

Beginning with a survey of the state-of-the-art of processing remotely sensed data in early 1975, significant developments between that time and the present are chronicled, and technologies for early 1979 are projected. Current technical issues discussed include: training selection and labeling; classification and mensuration; use of satellite indicators to supplement predictions; small scale field structures; physical factors; ancillary data; geometric quality; and the cost of processing.

Holmes, Q. A.↗
NASA NTRS2021

Data Processing of Miniaturized Laser Heterodyne Radiometer (mini-LHR) Ground Instrument Retrievals

The Miniaturized Laser Heterodyne Radiometer (mini-LHR) is a passive ground instrument that observes the mole fraction of carbon dioxide (CO) and methane (CH)in the atmospheric column by measuring their absorption of sunlight at 1.6 microns. A laser heterodyne radiometer is similar in design to the super heterodyne radio receiver that is well known by ham radio enthusiasts. While not previously a commercial technique, laser heterodyne radiometers have a history of measuring atmospheric trace gases that started in the 1960s. With the commercial availability of inexpensive, low-power, thumbnail-sized lasers developed for the telecommunications industry, it was possible to miniaturize this technique and ultimately commercialize it. The mini-LHR has been under development at NASA GSFC since 2009. During that time, in addition to signicant technical improvements, processing has also evolved and been streamlined. Here we present details of the processing approach for raw mini-LHR data to produce 30- and 60-minute data products of CH and CO column mole fractions. Processing occurs in two general stages: a python-based pre-processing of raw data, followed by ingestion into a Planetary Spectrum Generator (PSG) retrieval algorithm. Raw data processing involves removal of outliers, correcting for changes in air mass throughout the day, averaging scans, and ultimately converting averaged scans into transmittance vs. wavelength. The PSG retrieval simulates a spectra for the time/day/location of the scan with meteorological inputs from Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) data set and then perturbs the concentrations of CO and CH to obtain a t based on an iterative least-squares curve fitting procedure.

Giancarlo Roberto Zambrano↗
NASA NTRS1973

Image data processing system requirements study. Volume 1: Analysis

Digital image processing, image recorders, high-density digital data recorders, and data system element processing for use in an Earth Resources Survey image data processing system are studied. Loading to various ERS systems is also estimated by simulation.

Honikman, T.↗