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At least 397 records · Page 22

Spacecraft contamination investigation by direct simulation Monte Carlo - Contamination on UARS/HALOE

A three-dimensional version of the direct simulation Monte Carlo method is adapted to study the contamination environment surrounding a highly detailed model of the Upper Atmosphere Research Satellite, with the ultimate goal of estimating the cumulative level of molecular deposits on critical optical surfaces of the Halogen Occultation Experiment. Emphasis is placed on describing the development of preprocessing codes that simplify the incorporation of geometry and outgassing data into the main run code. A novel use of parallel processing software allows use of multiple processors to solve different regions of the overall flowfield. Initial results relating to contaminant cloud structure, cloud composition, and statistics of simulated molecules impinging on the Halogen Occultation telescope's aperture plane are presented, along with data related to code performance.

Rault, Didier F. G.↗

Applications of artificial intelligence 1993: Knowledge-based systems in aerospace and industry; Proceedings of the Meeting, Orlando, FL, Apr. 13-15, 1993

The present volume on applications of artificial intelligence with regard to knowledge-based systems in aerospace and industry discusses machine learning and clustering, expert systems and optimization techniques, monitoring and diagnosis, and automated design and expert systems. Attention is given to the integration of AI reasoning systems and hardware description languages, care-based reasoning, knowledge, retrieval, and training systems, and scheduling and planning. Topics addressed include the preprocessing of remotely sensed data for efficient analysis and classification, autonomous agents as air combat simulation adversaries, intelligent data presentation for real-time spacecraft monitoring, and an integrated reasoner for diagnosis in satellite control. Also discussed are a knowledge-based system for the design of heat exchangers, reuse of design information for model-based diagnosis, automatic compilation of expert systems, and a case-based approach to handling aircraft malfunctions.

Fayyad, Usama M.↗

Upper tropospheric water vapor features observed in the 1980's using the 6.7 and 7.2 micron TOVS channels

The NOAA has been preprocessing the TIROS Operational Vertical Sounder (TOVS) IR and microwave channels to correct for cloud amount, spot size, and viewing angle. An examination is now being conducted of the 6-7 micron water vapor band; a preliminary evaluation is here presented of the regional and global features of this large data base on daily, monthly, annual, and decadal time scales. The TOVS archives allow large-scale climatological features to be established.

Chesters, Dennis↗

Alaska SAR processor implementation of E-ERS-1

The synthetic aperture radar (SAR) data processing algorithm used by the Alaska SAR Facility (ASF) for the European Space Agency's first Remote-Sensing Satellite (E-ERS-1) SAR data are examined. Preprocessing highlights two features: signal measurement, which includes signal-to-noise ratio, replica measurement, and noise measurement; and Doppler measurement, which includes clutter lock and autofocus. The custom pipeline architecture performs the main processing with controls at the input interface, range correlator, corner-turn memory, azimuth correlator, and multi-look memory. The control software employs a flexible control scheme. The Committee on Earth Observation Satellites (CEOS) format encapsulates the ASF products. System performance for SAR image processing of E-ERS-1 data is reviewed.

Cuddy, David↗

The effect of spatial resolution upon cloud optical property retrievals. I - Optical thickness

High spectral and spatial resolution Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) imagery is used to study the effects of spatial resolution upon fair weather cumulus cloud optical thickness retrievals. As a preprocessing step, a variation of the Gao and Goetz three-band ratio technique is used to discriminate clouds from the background. The combination of the elimination of cloud shadow pixels and using the first derivative of the histogram allows for accurate cloud edge discrimination. The data are progressively degraded from 20 m to 960 m spatial resolution. The results show that retrieved cloud area increases with decreasing spatial resolution. The results also show that there is a monotonic decrease in retrieved cloud optical thickness with decreasing spatial resolution. It is also demonstrated that the use of a single, monospectral reflectance threshold is inadequate for identifying cloud pixels in fair weather cumulus scenes and presumably in any inhomogeneous cloud field. Cloud edges have a distribution of reflectance thresholds. The incorrect identification of cloud edges significantly impacts the accurate retrieval of cloud optical thickness values.

Feind, Rand E.↗

Optimization of the information content of multitemporal Landsat TM data sets for monitoring forest cover disturbance

Procedures that were developed to optimize the information content of multitemporal thematic mapper (TM) data sets for forest cover disturbance monitoring in Minnesota are described. TM imagery from three different years was calibrated to exoatmospheric reflectance. An atmospheric correction routine was applied combining two major components, atmospheric normalization over time and transformation to ground reflectance. Atmospheric conditions were modeled over time using regression functions derived from five ground features known to be unchanged over the time interval of interest and spanning the entire image reflectance range. The correlation between digital data and the forest cover was subsequently maximized and irrelevant information content was reduced by converting the band-specific reflectances into seven vegetation indices that were assumed to carry unique information. The application of two change detection algorithms to these seven indices ultimately resulted in 14 change features for each time interval of interest. Results show that the preprocessing sequence is vital to forest cover monitoring methodology.

Coppin, Pol R.↗

Generating local addresses and communication sets for data-parallel programs

Generating local addresses and communication sets is an important issue in distributed-memory implementations of data-parallel languages such as High Performance FORTRAN. We show that, for an array A affinely aligned to a template that is distributed across p processors with a cyclic(k) distribution and a computation involving the regular section A(l:h:s), the local memory access sequence for any processor is characterized by a finite state machine of at most k states. We present fast algorithms for computing the essential information about these state machines, and extend the framework to handle multidimensional arrays. We also show how to generate communication sets using the state machine approach. Performance results show that this solution requires very little run-time overhead and acceptable preprocessing time.

Chatterjee, Siddhartha↗

A prototype expert system in OPS5 for data error detection

A prototype expert system was developed in the OPS5 language to perform error checking on data which spacecraft builders/users supply to NASA GSFC for processing on the Communications Link Analysis and Simulation System (CLASS) computer. This prototype expert system, called Trajectory Preprocessing System (TRAPS), contains 49 rules and at present runs on an IBM PC in the OPS5+ software package from Artelligence, Inc. In its operational phase, TRAPS will run in the Oak Ridge Production Language (ORPL) on the CLASS computer (a Perkin-Elmer 3244 supermini). ORPL, an implementation of OPS5 by the Oak Ridge National Laboratory in MULTOFORTH on a Hewlett-Packard 9836 desktop computer, is now being ported to SS-FORTH on the CLASS computer. This paper discusses the expert system problem domain, development approach, tools, results and future plans stemming from the TRAPS project.

Rash, James↗

Fourier domain target transformation analysis in the thermal infrared

Remote sensing uses of principal component analysis (PCA) of multispectral images include band selection and optimal color selection for display of information content. PCA has also been used for quantitative determination of mineral types and abundances given end member spectra. The preliminary results of the investigation of target transformation PCA (TTPCA) in the fourier domain to both identify end member spectra in an unknown spectrum, and to then calculate the relative concentrations of these selected end members are presented. Identification of endmember spectra in an unknown sample has previously been performed through bandmatching, expert systems, and binary classifiers. Both bandmatching and expert system techniques require the analyst to select bands or combinations of bands unique to each endmember. Thermal infrared mineral spectra have broad spectral features which vary subtly with composition. This makes identification of unique features difficult. Alternatively, whole spectra can be used in the classification process, in which case there is not need for an expert to identify unique spectra. Use of binary classifiers on whole spectra to identify endmember components has met with some success. These techniques can be used, along with a least squares fit approach on the endmembers identified, to derive compositional information. An alternative to the approach outlined above usese target transformation in conjunction with PCA to both identify and quantify the composition of unknown spectra. Preprocessing of the library and unknown spectra into the fourier domain, and using only a specific number of the components, allows for significant data volume reduction while maintaining a linear relationship in a Beer's Law sense. The approach taken here is to iteratively calculate concentrations, reducing the number of endmember components until only non-negative concentrations remain.

Anderson, D. L.↗

A review and analysis of neural networks for classification of remotely sensed multispectral imagery

A literature survey and analysis of the use of neural networks for the classification of remotely sensed multispectral imagery is presented. As part of a brief mathematical review, the backpropagation algorithm, which is the most common method of training multi-layer networks, is discussed with an emphasis on its application to pattern recognition. The analysis is divided into five aspects of neural network classification: (1) input data preprocessing, structure, and encoding; (2) output encoding and extraction of classes; (3) network architecture, (4) training algorithms; and (5) comparisons to conventional classifiers. The advantages of the neural network method over traditional classifiers are its non-parametric nature, arbitrary decision boundary capabilities, easy adaptation to different types of data and input structures, fuzzy output values that can enhance classification, and good generalization for use with multiple images. The disadvantages of the method are slow training time, inconsistent results due to random initial weights, and the requirement of obscure initialization values (e.g., learning rate and hidden layer size). Possible techniques for ameliorating these problems are discussed. It is concluded that, although the neural network method has several unique capabilities, it will become a useful tool in remote sensing only if it is made faster, more predictable, and easier to use.

Paola, Justin D.↗

Visualization techniques to aid in the analysis of multi-spectral astrophysical data sets

The goal of this project was to support the scientific analysis of multi-spectral astrophysical data by means of scientific visualization. Scientific visualization offers its greatest value if it is not used as a method separate or alternative to other data analysis methods but rather in addition to these methods. Together with quantitative analysis of data, such as offered by statistical analysis, image or signal processing, visualization attempts to explore all information inherent in astrophysical data in the most effective way. Data visualization is one aspect of data analysis. Our taxonomy as developed in Section 2 includes identification and access to existing information, preprocessing and quantitative analysis of data, visual representation and the user interface as major components to the software environment of astrophysical data analysis. In pursuing our goal to provide methods and tools for scientific visualization of multi-spectral astrophysical data, we therefore looked at scientific data analysis as one whole process, adding visualization tools to an already existing environment and integrating the various components that define a scientific data analysis environment. As long as the software development process of each component is separate from all other components, users of data analysis software are constantly interrupted in their scientific work in order to convert from one data format to another, or to move from one storage medium to another, or to switch from one user interface to another. We also took an in-depth look at scientific visualization and its underlying concepts, current visualization systems, their contributions, and their shortcomings. The role of data visualization is to stimulate mental processes different from quantitative data analysis, such as the perception of spatial relationships or the discovery of patterns or anomalies while browsing through large data sets. Visualization often leads to an intuitive understanding of the meaning of data values and their relationships by sacrificing accuracy in interpreting the data values. In order to be accurate in the interpretation, data values need to be measured, computed on, and compared to theoretical or empirical models (quantitative analysis). If visualization software hampers quantitative analysis (which happens with some commercial visualization products), its use is greatly diminished for astrophysical data analysis. The software system STAR (Scientific Toolkit for Astrophysical Research) was developed as a prototype during the course of the project to better understand the pragmatic concerns raised in the project. STAR led to a better understanding on the importance of collaboration between astrophysicists and computer scientists.

Brugel, Edward W.↗

New progress of ranging technology at Wuhan Satellite Laser Ranging Station

A satellite laser ranging system with an accuracy of the level of centimeter has been successfully developed at the Institute of Seismology, State Seismological Bureau with the cooperation of the Institute of Geodesy and Geophysics, Chinese Academy of Science. With significant improvements on the base of the second generation SLR system developed in 1985, ranging accuracy of the new system has been upgraded from 15 cm to 3-4 cm. Measuring range has also been expanded, so that the ETALON satellite with an orbit height of 20,000 km launched by the former U.S.S.R. can now be tracked. Compared with the 2nd generation SLR system, the newly developed system has the following improvements. A Q modulated laser is replaced by a mode-locked YAG laser. The new device has a pulse width of 150 ps and a repetition rate of 1-4 pps. A quick response photomultiplier has been adopted as the receiver for echo; for example, the adoption of the MCP tube has obviously reduced the jitter error of the transit time and has improved the ranging accuracy. The whole system is controlled by an IBM PC/XT Computer to guide automatic tracking and measurement. It can carry out these functions for satellite orbit calculation, real-time tracking and adjusting, data acquisition and the preprocessed of observing data, etc. The automatization level and reliability of the observation have obviously improved.

Xia, Zhiz-Hong↗

Generating local addresses and communication sets for data-parallel programs

Generating local addresses and communication sets is an important issue in distributed-memory implementations of data-parallel languages such as High Performance Fortran. We show that for an array A affinely aligned to a template that is distributed across p processors with a cyclic(k) distribution, and a computation involving the regular section A, the local memory access sequence for any processor is characterized by a finite state machine of at most k states. We present fast algorithms for computing the essential information about these state machines, and extend the framework to handle multidimensional arrays. We also show how to generate communication sets using the state machine approach. Performance results show that this solution requires very little runtime overhead and acceptable preprocessing time.

Chatterjee, Siddhartha↗

Laser ranging data analysis

Center for Space Research efforts have focused on the near real-time analysis of Lageos laser ranging data and on the production of predictive ephemerides. The data are analyzed in terms of range bias, time bias, and internal precision, and estimates for the Earth orientation parameters X(sub p), Y(sub p) and UT1 are obtained. The results of these analyses are reported in a variety of formats. In addition several additional stations began sending not only quick-look observations but also normal points created on-site with new software. These normal points are transmitted in a new standard format different from either current quick-look or MERIT-II full-rate formats. Thus new preprocessing software was written and successfully tested on these data. Inspection of the Bendix produced Lageos full-rate normal points continued, with detailed analyses and filtering of all 1991 A and B release normal points for Lageos through the beginning of 1992. A summary of the combined full-rate and quick-look normal point data set created for 1991 is provided. New long-term ephemerides for Lageos satellite, as well as for Etalon-1 and Etalon-2 (the so-called high satellites used for laser ranging) were produced and distributed to the network stations in cooperation with the Crustal Dynamics Project and Eurolas. These predictions are used by essentially every laser ranging site obtaining regular returns from any of these three satellites.

Source record↗

Measurement selection for parametric IC fault diagnosis

Experimental results obtained with the use of measurement reduction for statistical IC fault diagnosis are described. The reduction method used involves data pre-processing in a fashion consistent with a specific definition of parametric faults. The effects of this preprocessing are examined.

Wu, A.↗

Nature's crucible: Manufacturing optical nonlinearities for high resolution, high sensitivity encoding in the compound eye of the fly, Musca domestica

The number of pixels per unit area sampling an image determines Nyquist resolution. Therefore, the highest pixel density is the goal. Unfortunately, as reduction in pixel size approaches the wavelength of light, sensitivity is lost and noise increases. Animals face the same problems and have achieved novel solutions. Emulating these solutions offers potentially unlimited sensitivity with detector size approaching the diffraction limit. Once an image is 'captured', cellular preprocessing of information allows extraction of high resolution information from the scene. Computer simulation of this system promises hyperacuity for machine vision.

Wilcox, Mike↗

Deep near-infrared survey of the Southern Sky (DENIS)

DENIS (Deep Near-Infrared Survey of the Southern Sky) will be the first complete census of astronomical sources in the near-infrared spectral range. The challenges of this novel survey are both scientific and technical. Phenomena radiating in the near-infrared range from brown dwarfs to galaxies in the early stages of cosmological evolution, the scientific exploitation of data relevant over such a wide range requires pooling expertise from several of the leading European astronomical centers. The technical challenges of a project which will provide an order of magnitude more sources than given by the IRAS space mission, and which will involve advanced data-handling and image-processing techniques, likewise require pooling of hardware and software resources, as well as of human expertise. The DENIS project team is composed of some 40 scientists, computer specialists, and engineers located in 5 European Community countries (France, Germany, Italy, The Netherlands, and Spain), with important contributions from specialists in Australia, Brazil, Chile, and Hungary. DENIS will survey the entire southern sky in 3 colors, namely in the I band at a wavelength of 0.8 micron, in the 1.25 micron J band, and in the 2.15 micron K' band. The sensitivity limits will be 18th magnitude in the I band, 16th in the J band, and 14.5th in the K' band. The angular resolution achieved will be 1 arcsecond in the I band, and 3.0 arcseconds in the J and K' bands. The European Southern Observatory 1 m telescope on La Silla will be dedicated to survey use during operations expected to last four years, commencing in late 1993. DENIS aims to provide the astronomical community with complete digitized infrared images of the full southern sky and a catalogue of extracted objects, both of the best quality and in readily accessible form. This will be achieved through dedicated software packages and specialized catalogues, and with assistance from the Leiden and Paris Data Analysis Centers. The data will be mailed on DAT tapes from La Silla to the two Data Analysis Centers for further processing. Two centers are necessary because of the shear quantity of data and because of the complementary roles the Centers will develop, each exploiting its own particular expertise. The Leiden Data Analysis Center (LDAC) will extract objects, establish their parameters, and archive them into a source catalogue. The LDAC will collaborate with the Groningen Space Research group that has gained experience in infrared image handling from the IRAS satellite. The Paris Data Analysis Center (PDAC) will be responsible for archiving and preprocessing the raw data to provide a homogeneous set of data suitable for further reduction in both the Leiden and Paris data analysis streams. The PDAC will also extract and archive images for the sources flagged by the LDAC as extended, and create a catalogue of galaxies. In exploiting the DENIS data we foresee the collaboration with other data analysis centers, such as the Observatoire de Lyon where the relevant DENIS catalogue of galaxies can be incorporated into their extragalactic database. The Point Sources and the Small Extended Sources catalogues could be incorporated in the Late Type Star database at Montpellier, and in the SIMBAD database as CDS. At Groningen the IRAS Point Source catalogue and/or image data can be merged with the DENIS catalogues. At Meudon algorithms and software will be developed with main goal assessing the limits reachable for the homogeneity and intrinsic consistency between the ensemble of the images in the data base (flat-fielding, relative positioning of the fields, bootstrapped flux calibration) but also for the data analysis.

Deul, E.↗

A generic archive protocol and an implementation

Archiving vast amounts of data has become a major part of every scientific space mission today. The Generic Archive/Retrieval Services Protocol (GRASP) addresses the question of how to archive the data collected in an environment where the underlying hardware archives may be rapidly changing. GRASP is a device independent specification defining a set of functions for storing and retrieving data from an archive, as well as other support functions. GRASP is divided into two levels: the Transfer Interface and the Action Interface. The Transfer Interface is computer/archive independent code while the Action Interface contains code which is dedicated to each archive/computer addressed. Implementations of the GRASP specification are currently available for DECstations running Ultrix, Sparcstations running SunOS, and microVAX/VAXstation 3100's. The underlying archive is assumed to function as a standard Unix or VMS file system. The code, written in C, is a single suite of files. Preprocessing commands define the machine unique code sections in the device interface. The implementation was written, to the greatest extent possible, using only ANSI standard C functions.

Jordan, J. M.↗