KEYWORDS: Data acquisition, Data modeling, Sensors, Distributed computing, Data processing, Databases, Systems modeling, Data archive systems, Process modeling, Image processing
Digitization of the battlespace for current and future combat systems cannot be complete without effective weather intelligence products and decision aids. An important challenge facing current weather intelligence products involves the simultaneous collection and dissemination of the vast amounts of raw and processed meteorological data. Data can originate from various types of sensors, sources, and computing models. Also, data collections can be sporadic and their publication can materialize on an assortment of formats and through dissimilar channels. To resolve many of these challenges, we have investigated a tuple-spaces solution that provides lose-coupling of sensors, systems, and weather forecasting models in a networked environment. Of interest are the results of experiments that employ the Jini/JavaSpaces implementation to resolve the problems of data acquisition and dissemination. This paper will present our space-based design to loosely-couple several weather sensors and simultaneously acquire their data at high output rates. Our results show that tuple-spaces implementations simplify acquisition and distribution of weather intelligence information. Other experimental results will demonstrate that a space-based architecture can also be employed by other network centric systems that involve information dissemination, decision aids, and collaboration/computing environments.
Rapid advances in computer image generators (CIGs) and scene animating software facilitate the completion of important objectives in the distributed interactive simulation effort. One objective has been to produce an accurate simulation of meteorological visibility through the use of fog or blending functions. Silicon Graphics' (SGI) Performer software capabilities, for example, are shown here to be capable of correctly generating visibility and haze in real-time scenes if one applies certain physical definitions in conjunction with certain corrections to the SGI Performer software. This paper first presents a brief background on the physical basis of meteorological visibility. Then, it quantifies and tests the direct relationship between the scene generator's parameters for the `atmospheric fading coefficient' and the meteorological visibility. An important fix to the Performer's fog function is described and the results of our implementation of a meteorological visibility `calibration' are presented.
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