Information Science

Protocols for Handling Messages Between Simulation Computers

Both time-critical and delivery-critical characteristics are accommodated. Practical Simulator Network (PSimNet) is a set of data communication protocols designed especially for use in handling messages between computers that are engaging cooperatively in real time or nearly real time training simulations. In a typical application, computers that provide individualized training at widely dispersed locations would communicate,by use of PSimNet, with a central host computer that would provide a common computational simulation environment and common data. Originally intended for use in supporting interfaces between training computers and computers that simulate the responses of spacecraft scientific payloads, PSimNet could be especially well suited for a variety of other applications — for example, group automobile driver training in a classroom. Another potential application might lie in networking of automobile diagnostic computers at repair facilities to a central computer that would compile the expertise of numerous technicians and engineers and act as an expert consulting technician.

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Algorithms for Maneuvering Spacecraft Around Small Bodies

A document describes mathematical derivations and applications of autonomous guidance algorithms for maneuvering spacecraft in the vicinities of small astronomical bodies like comets or asteroids. These algorithms compute fuel- or energy-optimal trajectories for typical maneuvers by solving the associated optimal-control problems with relevant control and state constraints. In the derivations, these problems are converted from their original continuous (infinite-dimensional) forms to finite-dimensional forms through (1) discretization of the time axis and (2) spectral discretization of control inputs via a finite number of Chebyshev basis functions. In these doubly discretized problems, the Chebyshev coefficients are the variables. These problems are, variously, either convex programming problems or programming problems that can be convexified. The resulting discrete problems are convex parameter-optimization problems; this is desirable because one can take advantage of very efficient and robust algorithms that have been developed previously and are well established for solving such problems. These algorithms are fast, do not require initial guesses, and always converge to global optima. Following the derivations, the algorithms are demonstrated by applying them to numerical examples of fly-by, descent-to-hover, and ascent-from-hover maneuvers.

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Improved Solar-Radiation-Pressure Models for GPS Satellites

A report describes a series of computational models conceived as an improvement over prior models for determining effects of solar-radiation pressure on orbits of Global Positioning System (GPS) satellites.  These models are based on fitting coefficients of Fourier functions of Sun-spacecraft- Earth angles to observed spacecraft orbital motions. Construction of a model in this series involves the following steps:

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Fast Lossless Compression of Multispectral-Image Data

A low-complexity adaptive-filtering algorithm is used. An algorithm that effects fast lossless compression of multispectral-image data is based on low-complexity, proven adaptive filtering algorithms. This algorithm is intended for use in compressing multispectral-image data aboard spacecraft for transmission to Earth stations. Variants of this algorithm could be useful for lossless compression of three-dimensional medical imagery and, perhaps, for compressing image data in general.

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Discerning Trends in Performance Across Multiple Events

Mass Data is a computer program that enables rapid, easy discernment of trends in performance data across multiple flights and ground tests. The program can perform Fourier analysis and other functions for the purposes of frequency analysis and trending of all variables. These functions facilitate identification of past use of diagnosed systems and of anomalies in such systems, and enable rapid assessment of related current problems. Many variables, for computation of which it is usually necessary to perform extensive manual manipulation of raw downlist data, are automatically computed and made available to all users, regularly eliminating the need for what would otherwise be an extensive amount of engineering analysis. Data from flight, ground test, and simulation are preprocessed and stored in one central location for instantaneous access and comparison for diagnostic and trending purposes. Rules are created so that an event log is created for every flight, making it easy to locate information on similar maneuvers across many flights. The same rules can be created for test sets and simulations, and are searchable, so that information on like events is easily accessible.

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Assistant for Analyzing Tropical Rain Mapping Radar Data

A document is defined that describes an approach for a Tropical Rain Mapping Radar Data System (TDS). TDS is composed of software and hardware elements incorporating a two-frequency spaceborne radar system for measuring tropical precipitation. The TDS would be used primarily in generating data products for scientific investigations. The most novel part of the TDS would be expert-system software to aid in the selection of algorithms for converting raw radar-return data into such primary observables as rain rate, path integrated rain rate, and surface backscatter. The expert-system approach would address the issue that selection of algorithms for processing the data requires a significant amount of preprocessing, non-intuitive reasoning, and heuristic application, making it infeasible, in many cases, to select the proper algorithm in real time. In the TDS, tentative selections would be made to enable conversions in real time. The expert system would remove straightforwardly convertible data from further consideration, and would examine ambiguous data, performing analysis in depth to determine which algorithms to select. Conversions performed by these algorithms, presumed to be correct, would be compared with the corresponding real-time conversions. Incorrect real-time conversions would be updated using the correct conversions.

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Less-Complex Method of Classifying MPSK

Nearly optimal performance can be obtained with less computation. An alternative to an optimal method of automated classification of signals modulated with M-ary phase-shift-keying (M-ary PSK or MPSK) has been derived. The alternative method is approximate, but it offers nearly optimal performance and entails much less complexity, which translates to much less computation time.

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