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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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The Next-Generation Precipitation Radar (PR-2) prototyped by NASA/JPL will depend heavily on high-performance digital processing to collect meaningful echo data.
The characterization study has shown that adjustments in an application's data accesses can easily create a performance difference of three or more times in actual applications. In general, by iterating over a small portion of a data set rather than its entirety, execution can remain within cache thereby producing a performance increase. Additionally, the approaches used in performing I/O can make a major performance difference.
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This report summarizes the results of a series of tests to characterize catastrophic radiation-induced latchup in the DSP2100, which is used in three different applications on MLS.
The Next-Generation Precipitation Radar prototyped by NASA/JPL will depend heavily on high performance digital processing to collect meaningful rain echo data.
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The Alaska SAR Facility (ASF) located at the University of Alaska Fairbanks (UAF) has been in operations since 1991 serving as a key data acquisition, processing, archive and distribution center for a number of polar orbiting SAR (synthetic aperture radar) satelittes including ERS 1/2 and JERS-1.
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A particularily challenging image processing application is the real time scene acquisition and object discrimination. It requires spatio-temporal recognition of point and resolved objects at high speeds with parallel processing algorithms. Neural network paradigms provide fine grain parallism and, when implemented in hardware, offer orders of magnitude speed up. However, neural networks implemented on a VLSI chip are planer architectures capable of efficient processing of linear vector signals rather than 2-D images. Therefore, for processing of images, a 3-D stack of neural-net ICs receiving planar inputs and consuming minimal power are required. Details of the circuits with chip architectures will be described with need to develop ultralow-power electronics. Further, use of the architecture in a system for high-speed processing will be illustrated.
In pattern recognition and classification for spatio-temporal problems, one of the most challenging tasks is to provide a good and valid solution in real-time. Because of time constraints, software-based neural network approaches may not be suitable for practical use. Hardware solutions seem to be good candidates for this class of problems. Currently, the Three Dimensional Analog Neural Network (3-DANN) is an effective approach to solving spatio-temporal problems in three-dimensional hardware.
The Alaska SAR Facility is currently undergoing an upgrade development effort to accommodate the upcoming ERS-2 and RADARSAT satellites.
We propose a Lagrangian ice motion tracker to follow the trajectory of ice particles at initially fixed grid points in the winter Arctic.
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