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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
NASA NTRS2020

Use of an Internal Mercury-Argon Lamp for the Calibration of Raman Frequency in Large Raman Images of Astromaterials

Raman imaging is an emerging tool for the analysis of meteorites, as it is capable of describing mineralogy, carbon composition/speciation, and crystal orientation all within a petrographic context. Adequately examining the heterogeneous composition of a meteorite, while maintaining low laser powers needed to prevent damage to meteorite mineralogy and organics, often requires the collection of large Raman images with long collection times on the timescale of days. However, the frequency calibration of the Raman instrument/spectrometer drifts on long timescales resulting in low frequency precision for the Raman spectra comprising a large Raman image. This decrease in frequency precision can compromise the analysis of geological markers that can provide important information on a meteorite sample. We examine, in detail, the change in bandwidth and frequency of the Raman bands and Hg-Ar emission lines in our Raman images as a function of time and laboratory temperature. To overcome the drift in calibration, we utilize a commercial WITec Raman instrument with an internal Hg-Ar calibration lamp to individually calibrate each spectrum in the Raman image. Our instrument, known as “Ratatoskr”, uses a beam splitter in place of the customary mirror to facilitate collection of Hg-Ar calibration lines concurrent with Raman spectra. We show that using the internal calibration we can improve the frequency precision for the spectra in our Raman images from ~±0.15 cm(exp -1) to ~±0.05 cm(exp -1) for Raman spectra collected over multiple days. This is important as it improves measurements of mineral chemistry, latent strain, and other features that are dependent upon accurate peak position determination. We also examine the spectral signal-to-noise ratio needed to minimize the frequency error when fitting bands to Gaussian/Lorentzian profiles. We then use our results to suggest a general method for calibrating the frequency of Raman spectra in large Raman images.

Jakubek, Ryan S.↗
NASA NTRSDate not supplied

Linear Stokes Measurement of Thermal Targets using Compact LWIR Spectropolarimeter

The trade-o↵ between spectral resolution and instrument throughput is analyzed for a compact, uncooled, longwave infrared (LWIR) channeled spectropolarimeter (IRCSP). The IRCSP was developed as a part of the Submm Wave and InfraRed Polarimeters (SWIRP) project out of NASA’s Goddard Spaceflight Center. The IRCSP scientific objective targets measurements of AOLP and DOLP with 1-μm spectral resolution from 8.5 - 12.5 μm in a single snapshot. The geometry of the field stop determines the field of view (FOV) of the IRCSP. This work relates the spectral resolution, instrument throughput, and polarimetric accuracy of a spectro-polarimeter to the FOV. The accuracy of linear Stokes retrievals for low temperature thermal targets are predicted for varying FOV and measurement noise conditions. This work presents a method to quantify the achievable accuracy in AOLP and DOLP as a function of field stop dimensions and signal-to-noise ratio (SNR). While smaller field stops are shown to improve accuracy as the spectral resolution is increased, low SNR is the dominant source of error for the IRCSP prototype. For the IRCSP, a SNR of at least 80 is required to produce DOLP measurements with < 5% error for targets with DOLP < 0.2.

LWIR↗
NASA NTRS1993

Mixing model analysis of telescopic lunar spectra

We have analyzed very high quality reflectance spectra of the lunar surface from the University of Hawaii lunar spectral data collection using a spectral mixing model. The spectra analyzed are those of 45 mare sites and 75 highland sites. The spectra were selected on the basis of very high signal to noise ratios based on error bars and point to point scatter, and on quality of removal of telluric water bands. The spectral mixing model used 7 components, not all of which were used in each fit. Four of the components were mineral spectra of the orthopyroxene, a clinopyroxene, an olivine and an anorthite, measured at the Brown University's RELAB. All of the minerals were 45-90 micron splits. Lunar soil contains other components which have the effect of reddening and darkening the soil as well as reducing spectral contrast. In addition, lunar soil contains spectral neutral bright material (likely very fine grained feldspar) which serves to reduce spectral contrast and brighten soils. Early attempts to fit many of the spectra pointed out the need for a component which has a very broad smooth absorption feature centered near 1.1 microns. Glass is a good candidate for this component. For the bright component we used a flat reflectance of 70 percent to represent fine grained feldspar. For the 'glass' component we used a telescopic spectrum of a pyroclastic glass present on the Aristarchus plateau which is characterized by a strong smooth band centered at 1.07 microns. In addition to exhibiting the glass band this spectrum is very red and has a low albedo. On the assumption that the dark component and the red component are agglutinates, which is reasonable but not necessarily true, we sought a dark red component. To derive its properties we modelled the spectrum of an Apollo 16 soil (16xxx) and assumed the dark red component to comprise 60 percent of the soil, appropriate to agglutinate abundance in mature soil. We adjusted the albedo and slope of a straight line representing the dark red component until the contrast and albedo of the model spectrum matched the soil spectrum. The mixing was done after conversion to a single scattering albedo.

Lucey, Paul G.↗
NASA NTRS1992

Learning class descriptions from a data base of spectral reflectance with multiple view angles

A learning program has been developed which combines 'learning by example' with the generate-and-test paradigm to furnish a robust learning environment capable of handling error-prone data. The problem is shown to be capable of learning class descriptions from positive and negative training examples of spectral and directional reflectance data taken from soil and vegetation. The program, which used AI techniques to automate very tedious processes, found the sequence of relationships that contained the most important information which could distinguish the classes.

Kimes, Daniel S.↗
NASA NTRS2011

Spectral Kernel Approach to Study Radiative Response of Climate Variables and Interannual Variability of Reflected Solar Spectrum

The radiative kernel approach provides a simple way to separate the radiative response to different climate parameters and to decompose the feedback into radiative and climate response components. Using CERES/MODIS/Geostationary data, we calculated and analyzed the solar spectral reflectance kernels for various climate parameters on zonal, regional, and global spatial scales. The kernel linearity is tested. Errors in the kernel due to nonlinearity can vary strongly depending on climate parameter, wavelength, surface, and solar elevation; they are large in some absorption bands for some parameters but are negligible in most conditions. The spectral kernels are used to calculate the radiative responses to different climate parameter changes in different latitudes. The results show that the radiative response in high latitudes is sensitive to the coverage of snow and sea ice. The radiative response in low latitudes is contributed mainly by cloud property changes, especially cloud fraction and optical depth. The large cloud height effect is confined to absorption bands, while the cloud particle size effect is found mainly in the near infrared. The kernel approach, which is based on calculations using CERES retrievals, is then tested by direct comparison with spectral measurements from Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY) (a different instrument on a different spacecraft). The monthly mean interannual variability of spectral reflectance based on the kernel technique is consistent with satellite observations over the ocean, but not over land, where both model and data have large uncertainty. RMS errors in kernel ]derived monthly global mean reflectance over the ocean compared to observations are about 0.001, and the sampling error is likely a major component.

Jin, Zhonghai↗
NASA NTRS1992

The density evolution of IRAS galaxies

A maximum likelihood test for density evolution is applied to a full-sky redshift survey of 5297 galaxies selected from the IRAS data base and flux-limited at 1.2 Jy. No evidence for evolution is found. Attention is given to important systematic errors which decrease the certainty with which evolution can be measured, namely, limited knowledge of the cosmological model, the unknown intrinsic spectral energy distribution of IRAS galaxies from 16 to 140 microns, the effect of density fluctuations, a Malmquist-like bias arising from flux errors in the IRAS Point Source Catalog, and possible incompleteness of the sample at high redshifts and low Galactic latitudes. It is shown that the Malmquist bias could result in a significant overestimation of the evolution rate, especially if the catalog has a flux limit near the completion limit of the Point Source Catalog.

Fisher, Karl B.↗
NASA NTRS1973

A multi-spectral method for estimating cirrus cloud top heights

A two-channel method has been developed to estimate the altitude of cirrus clouds over ocean areas with an expected altitude error less than or equal to plus or minus 50 mb. Reflected radiation is used to estimate cirrus emissivity in the 10- to 11-micron spectral interval. The cirrus altitude is determined from the emissivity estimate, a registered 10- to 11-micron measurement, and a vertical temperature profile. Nimbus 3 medium-resolution infrared radiometer measurements were used to establish the relationship between reflectance and 11-micron cirrus emissivity.

Shenk, W. E.↗
NASA NTRS2006

Processing Raman Spectra of High-Pressure Hydrogen Flames

The Raman Code automates the analysis of laser-Raman-spectroscopy data for diagnosis of combustion at high pressure. On the basis of the theory of molecular spectroscopy, the software calculates the rovibrational and pure rotational Raman spectra of H2, O2, N2, and H2O in hydrogen/air flames at given temperatures and pressures. Given a set of Raman spectral data from measurements on a given flame and results from the aforementioned calculations, the software calculates the thermodynamic temperature and number densities of the aforementioned species. The software accounts for collisional spectral-line-broadening effects at pressures up to 60 bar (6 MPa). The line-broadening effects increase with pressure and thereby complicate the analysis. The software also corrects for spectral interference ("cross-talk") among the various chemical species. In the absence of such correction, the cross-talk is a significant source of error in temperatures and number densities. This is the first known comprehensive computer code that, when used in conjunction with a spectral calibration database, can process Raman-scattering spectral data from high-pressure hydrogen/air flames to obtain temperatures accurate to within 10 K and chemical-species number densities accurate to within 2 percent.

Nguyen, Quang-Viet↗
NASA NTRS2006

Implementation of Cloud Retrievals for Tropospheric Emission Spectrometer (TES) Atmospheric Retrievals: Part 1. Description and Characterization of Errors on Trace Gas Retrievals

We develop an approach to estimate and characterize trace gas retrievals in the presence of clouds in high spectral measurements of upwelling radiance in the infrared spectral region (650-2260/cm). The radiance contribution of clouds is parameterized in terms of a set of frequency-dependent nonscattering optical depths and a cloud height. These cloud parameters are retrieved jointly with surface temperature, emissivity, atmospheric temperature, and trace gases such as ozone from spectral data. We demonstrate the application of this approach using data from the Tropospheric Emission Spectrometer (TES) and test data simulated with a scattering radiative transfer model. We show the value of this approach in that it results in accurate estimates of errors for trace gas retrievals, and the retrieved values improve over the initial guess for a wide range of cloud conditions. Comparisons are made between TES retrievals of ozone, temperature, and water to model fields from the Global Modeling and Assimilation Office (GMAO), temperature retrievals from the Atmospheric Infrared Sounder (AIRS), tropospheric ozone columns from the Goddard Earth Observing System (GEOS) GEOS-Chem, and ozone retrievals from the Total Ozone Mapping Spectrometer (TOMS). In each of these cases, this cloud retrieval approach does not introduce observable biases into TES retrievals.

aerosols↗
NASA NTRS1994

Use of multiple gauges and microwave attenuation of precipitation for satellite verification

In this paper both a microwave attenuation measurement along a horizontal line and multiple point gauge measurements are analyzed as possible ground-truth designs to validate satellite precipitation retrieval algorithms at the field of view spatial level (typically about 20 km). The design consists of comparing a sequence of pairs of contemporaneous measurements taken from the ground and from space. The authors examine theoretically the variance of expected differences between the two systems. The line average measurement leads to a smaller mean-square error compared to the case of a single point gauge, since some of the small-scale variability of the rain field is smoothed away by the line integration. The multiple point gauge measurements also give smaller mean-square error than that of a single point gauge. The centroid of the line and point gauge configurations are considered to be located randomly inside the field of view for different overpasses. A space-time spectral formalism is used with a noise-forced diffusive rain field to find the mean-square error. By considering instantaneous ground and satellite measurement pairs over about 50 visits when raining, we can reduce the expected error to approximately 10% of the standard deviation of climatological variability. This is considered to be a useful level of tolerance for identifying biases in the retrieval algorithms. It is found that the multiple point gauges (especially two gauges) are the economical ground-truth design compared to the microwave attenuation based on the mean-square error comparison. The major finding of this study is that a significant improvement over the point gauge is obtained by adding a single additional piece of information; adding more gauges or extending the line of attenuation is not an important improvement.

Ha, Eunho↗
NASA NTRS2009

Spatial Modulation Improves Performance in CTIS

Suitably formulated spatial modulation of a scene imaged by a computed-tomography imaging spectrometer (CTIS) has been found to be useful as a means of improving the imaging performance of the CTIS. As used here, "spatial modulation" signifies the imposition of additional, artificial structure on a scene from within the CTIS optics. The basic principles of a CTIS were described in "Improvements in Computed- Tomography Imaging Spectrometry" (NPO-20561) NASA Tech Briefs, Vol. 24, No. 12 (December 2000), page 38 and "All-Reflective Computed-Tomography Imaging Spectrometers" (NPO-20836), NASA Tech Briefs, Vol. 26, No. 11 (November 2002), page 7a. To recapitulate: A CTIS offers capabilities for imaging a scene with spatial, spectral, and temporal resolution. The spectral disperser in a CTIS is a two-dimensional diffraction grating. It is positioned between two relay lenses (or on one of two relay mirrors) in a video imaging system. If the disperser were removed, the system would produce ordinary images of the scene in its field of view. In the presence of the grating, the image on the focal plane of the system contains both spectral and spatial information because the multiple diffraction orders of the grating give rise to multiple, spectrally dispersed images of the scene. By use of algorithms adapted from computed tomography, the image on the focal plane can be processed into an image cube a three-dimensional collection of data on the image intensity as a function of the two spatial dimensions (x and y) in the scene and of wavelength (lambda). Thus, both spectrally and spatially resolved information on the scene at a given instant of time can be obtained, without scanning, from a single snapshot; this is what makes the CTIS such a potentially powerful tool for spatially, spectrally, and temporally resolved imaging. A CTIS performs poorly in imaging some types of scenes in particular, scenes that contain little spatial or spectral variation. The computed spectra of such scenes tend to approximate correct values to within acceptably small errors near the edges of the field of view but to be poor approximations away from the edges. The additional structure imposed on a scene according to the present method enables the CTIS algorithms to reconstruct acceptable approximations of the spectral data throughout the scene.

Bearman, Gregory H.↗
NASA NTRS2018

Enhancements to the Open Access Spectral Band Adjustment Factor Online Calculation Tool for Visible Channels

With close to 40 years of satellite observations, from which, cloud, land-use, and aerosol parameters can be measured, inter-consistent calibrations are needed to normalize retrievals across satellite records. Various visible-sensor inter-calibration techniques have been developed that utilize radiometrically stable Earth targets, e.g., deep convective clouds and desert/polar ice pseudo-invariant calibration sites. Other equally effective, direct techniques for intercalibration between satellite imagers are simultaneous nadir overpass comparisons and ray-matched radiance pairs. Combining independent calibration results from such varied techniques yields robust calibration coefficients, and is a form of self-validation. One potential source of significant error when cross-calibrating satellite sensors, however, are the often small but substantial spectral discrepancies between comparable bands, which must be accounted for. As such, visible calibration methods rely on a Spectral Band Adjustment Factor (SBAF) to account for the spectral-response function- induced radiance differences between analogous imagers. The SBAF is unique to each calibration method as it is a function of the Earth-reflected spectra. In recent years, NASA Langley pioneered the use of SCIAMACHY-, GOME-2-, and Hyperion-retrieved Earth spectra to compute SBAFs. By carefully selecting hyperspectral footprints that best represent the conditions inherent to an inter-calibration technique, the uncertainty in the SBAF is greatly reduced. NASA Langley initially provided the Global Space-based Inter-calibration System processing and research centers with online SBAF tools, with which users select conditions to best match their calibration criteria. This article highlights expanded SBAF tool capabilities for visible wavelengths, with emphasis on the use of the spectral range filtering for the purpose of separating scene conditions for the channel that the SBAF is needed based on the reflectance values of other bands. In other words, spectral filtering will enable better scene-type selection for bands where scene determination is difficult without information from other channels, which should prove valuable to users in the calibration community.

Scarino, Benjamin↗
NASA NTRS1975

Balance between resolution and signal-to-noise ratio in scanner design for earth resources systems

An outline is presented of a method in which a sensor under design can be evaluated by comparison with an existing sensor of similar spectral response, providing certain performance characteristics are known. An approach for calculating errors in radiance measurements is discussed, giving attention to calibration, error caused by resolution factors, noise effects on accuracy, and combined radiance level accuracies for several scanner designs. The derivation of error caused by the modulation transfer function is also considered.

Norwood, V. T.↗
NASA NTRS1980

Search and rescue emergency locating transmitter detection/location procedure via TIROS satellite

A procedure is described which works effectively to detect and locate emergency locating transmitters (ELTs) and emergency position indicating radio beacons (EPIRBs) in a multisignal environment. Using data generated from several manufactured ELTs with diverse superimposed Doppler curves, as many as 9 simultaneous ELTs can be detected and located at a variety of signal strengths. It is noted that average position errors of 10 km are attainable today at signal power to noise spectral density ratios as low as 17 dB-Hz.

Wren, P. E.↗
NASA NTRS1982

The use of Landsat-3 thermal data to help differentiate land covers

Landsat-3 Multispectral Scanner Subsystem (MSS) digital data of the Baltimore, Maryland area gathered on May 24, 1978, are examined to show the usefulness of thermal data in providing better discrimination between agricultural and residential areas, certain types of urban/industrial areas and water, cloud shadows and water, and bare-extractive areas and bright urban cover types. High altitude aircraft imagery taken on May 3, 1978, provides ground truth and training site verification. Two classifications are made for each training site: the initial one using bands 4, 5, and 7 and a second in which the thermal data are included with the visible and near infrared data. This permits a direct comparison of areas spectrally similar with and without the inclusion of the thermal data. Commission errors determined from selected subsets of the data show reductions of 95% for the urban/industrial versus water themes, 84% for the residential versus agriculture themes, 64.0% for the bare-extractive versus bright urban themes, and 24% for the cloud shadow versus water themes when the thermal data are included in the signature.

Ormsby, J. P.↗
NASA NTRS1980

Analytical design of multispectral sensors

An optimal design based on the criterion of minimum mean square representation error using the Karhunen-Loeve expansion was developed to represent the spectral response functions from a stratum based upon a stochastic process scene model. From the overall pattern recognition system perspective, the effect of the representation accuracy on a typical performance criterion (the probability of correct classification) is investigated. The optimum sensor design provides a standard against which practical (suboptimum) operational sensors can be compared. An example design is provided and its performance is illustrated. Although developed primarily for the purpose of sensor design, the procedure has potential for making important contributions to scene understanding. Spectral channels which have narrow bandwidths relative to current sensor systems may be necessary to provide adequate spectral representation and improved classification performance.

Wiersma, D. J.↗
NASA NTRS1990

Energy spectra of cosmic rays above 1 TeV per nucleon

Direct measurements of cosmic-ray nuclei above 1 TeV/nucleon have been performed in a series of balloon-borne experiments with emulsion chambers. The observed all-particle spectrum above 20 TeV is consistent with the results of the Proton satellite and many air shower experiments. The proton spectrum is consistent with a power law having an index of 2.76 + or - 0.09 up to at least 100 TeV, but an overabundance of helium by a factor of 2 above 2 TeV per nucleon is found when compared with the extrapolation from the low energies. For heavy elements (C through Fe), the intensities around 1 TeV/nucleon are consistent, within the statistical errors, with the extrapolation from lower energy data using the Spacelab 2 spectral indices. An enhancement for the medium-heavy components (C through Ca) above 200 TeV is indicated. The mean mass above 50 TeV indicates slightly higher values than the results of the air shower experiments.

Burnett, T. H.↗