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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 NTRS1996

A technique for determining cloud free vs cloud contaminated pixels in satellite imagery

Since the first earth orbiting satellite sent pictures of the earth back to them, atmospheric scientists have been focused on the possibilities of using that information as both a forecasting tool and as a meteorological research tool. With the latest generation of Geostationary Operational Environmental Satellites (GOES) now entering service, that view of the earth yields views at a frequency and resolution never before available. These satellites have imagers with a five band multi-spectral capability with high spatial resolution. In addition, the sounder has eighteen thermal infrared (IR) channels plus one low-resolution visible band. With a resolution as small as one kilometer, GOES provides scientists with a powerful eye on the atmosphere. Menzel and Purdom (1994) detail both the imager and sounder capability as well as other systems on the GOES satellites. Immediately apparent in the visible channel are the patterns of clouds swirling over both oceans and continents. These clouds range in size from huge planetary systems covering thousands of kilometers to puffy fair weather cumulus clouds on the order of half a kilometer in size. With the IR sensors temperature patterns are observed. High clouds appear very cold, while low stratus field show temperatures near that of the surface. The surface, in turn, generally appears warmer than the clouds. It would seem then a simple manner to determine cloud and surface temperature from the imagery, but such is not the case. While most of the atmospheric constituents are well mixed and homogeneous, water vapor is not. The water molecule, because of its unique structure and vibration modes, affects the transmittance of the atmosphere most notably in the infrared regions. There are regions of the IR spectrum where water vapor acts as a strong absorber, and at others it is nearly transparent. The transparent wavelengths are called windows, and one such window occurs at 11.2 microns. Adjacent to this window at 12.7 microns which is strongly absorbed by water vapor. These two wavelengths form what is known as a split window, the utility of which was used. Using the linearized form of the radiative transfer equation, they were able to use the split window to determine the amount of water vapor present in the atmosphere. Jedlovec developed the physical split-window (PSW) technique which determines the integrated water content (IWC). The PSW method using Visible Infrared Spin Scan Radiometer (VISSR) Atmospheric Sounder (VAS) found on the older versions of the GOES satellites was used. Recently, Jedlovec and colleagues have been attempting to apply the PSW method using full disk IR imagery obtained by the new generation of GOES satellites. IWC is essential for improved analysis and prediction of convective storms which have been observed to develop in regions of both strong and rapidly evolving moisture gradients. It has also been used in the prediction of clouds and precipitation.

Wohlman, Richard A.↗
NASA NTRS1998

Pixel Paradise

PixelVision, Inc., has developed a series of integrated imaging engines capable of high-resolution image capture at dynamic speeds. This technology was used originally at Jet Propulsion Laboratory in a series of imaging engines for a NASA mission to Pluto. By producing this integrated package, Charge-Coupled Device (CCD) technology has been made accessible to a wide range of users.

Source record↗
NASA NTRS2005

Determination of Lateral Diffusivity in Single Pixel X-ray Absorbers with Implications for Position Dependent Excess Broadening

An ideal microcalorimeter is characterized by a constant energy resolution across the sensor's dynamic range. Any dependence of pulse shape on the position within the absorber where an event occurs leads to a degradation in resolution that is linear with event s energy (excess broadening). In this paper we present a numerical simulation that was developed to model the variation in pulse shape with position based on the thermal conductivity within the absorber and between the absorber, sensor, and heat bath, for arbitrarily shaped absorbers and sensors. All the parameters required for the simulation can be measured from actual devices. We describe how the thermal conductivity of the absorber material is determined by comparing the results of this model with data taken from a position sensitive detector in which any position dependent effect is purposely emphasized by making a long, narrow absorber that is read out by sensors on both end. Finally, we present the implications for excess broadening given the measured parameters of our X-ray microcalorimeters.

Saab, T.↗
NASA NTRS1993

Cosmic-ray Detector with Interdigitated-Finger Pixels for two-dimensional Position Information from a Singel Wafer Side

This paper describes a type of cosmic ray detector for isotopic and energy detection of energetic nuclei which derives both dimensions of position information from one side of the detector. This simplifies the required readout electronics, since only one precision amplifier connected to the other side is required for an accurate detection of the energy loss.

Cosmic-Ray Detector↗
NASA NTRS2000

Efficient color display using low-absorption in-pixel color filters

A display system having a non-absorbing and reflective color filtering array and a reflector to improve light utilization efficiency. One implementation of the color filtering array uses a surface plasmon filter having two symmetric metal-dielectric interfaces coupled with each other to produce a transmission optical wave at a surface plasmon resonance wavelength at one interface from a p-polarized input beam on the other interface. Another implementation of the color filtering array uses a metal-film interference filter having two dielectric layers and three metallic films.

Wang, Yu↗
NASA NTRS2002

Center of mass detection via an active pixel sensor

An imaging system for identifying the location of the center of mass (COM) in an image. In one aspect, an imaging system includes a plurality of photosensitive elements arranged in a matrix. A center of mass circuit coupled to the photosensitive elements includes a resistive network and a normalization circuit including at least one bipolar transistor. The center of mass circuit identifies a center of mass location in the matrix and includes: a row circuit, where the row circuit identifies a center of mass row value in each row of the matrix and identifies a row intensity for each row; a horizontal circuit, where the horizontal circuit identifies a center of mass horizontal value; and a vertical circuit, where the vertical circuit identifies a center of mass vertical value. The horizontal and vertical center of mass values indicate the coordinates of the center of mass location for the image.

Yadid-Pecht, Orly↗
NASA NTRS2003

Single chip camera active pixel sensor

A totally digital single chip camera includes communications to operate most of its structure in serial communication mode. The digital single chip camera include a D/A converter for converting an input digital word into an analog reference signal. The chip includes all of the necessary circuitry for operating the chip using a single pin.

Shaw, Timothy↗
NASA NTRS2005

Center of mass detection via an active pixel sensor

An imaging system for identifying the location of the center of mass (COM) in an image. In one aspect, an imaging system includes a plurality of photosensitive elements arranged in a matrix. A center of mass circuit coupled to the photosensitive elements includes a resistive network and a normalization circuit including at least one bipolar transistor. The center of mass circuit identifies a center of mass location in the matrix and includes: a row circuit, where the row circuit identifies a center of mass row value in each row of the matrix and identifies a row intensity for each row; a horizontal circuit, where the horizontal circuit identifies a center of mass horizontal value; and a vertical circuit, where the vertical circuit identifies a center of mass vertical value. The horizontal and vertical center of mass values indicate the coordinates of the center of mass location for the image.

Yadid-Pecht, Orly↗
NASA NTRS2006

Center of mass detection via an active pixel sensor

An imaging system for identifying the location of the center of mass (COM) in an image. In one aspect, an imaging system includes a plurality of photosensitive elements arranged in a matrix. A center of mass circuit coupled to the photosensitive elements includes a resistive network and a normalization circuit including at least one bipolar transistor. The center of mass circuit identifies a center of mass location in the matrix and includes: a row circuit, where the row circuit identifies a center of mass row value in each row of the matrix and identifies a row intensity for each row; a horizontal circuit, where the horizontal circuit identifies a center of mass horizontal value; and a vertical circuit, where the vertical circuit identifies a center of mass vertical value. The horizontal and vertical center of mass values indicate the coordinates of the center of mass location for the image.

Yadid-Pecht, Orly↗