Terrain database correlation is a major requirement for interoperability in distributed simulation. There are numerous situations in which terrain database correlation problems can occur that, in turn, lead to lack of interoperability in distributed training simulations. Examples are the use of different run-time terrain databases derived from inconsistent source data, the use of different resolutions, and the use of different data models between databases for both terrain and culture data. IST has been developing a suite of software tools, named ZCAP, to address terrain database interoperability issues. We discuss enhancements made to this suite, including improved algorithms for sampling and calculating line-of-sight, an improved method for measuring terrain roughness, and the application of a sparse matrix method to the terrain remediation solution developed at the Visual Systems Lab of the Institute for Simulation and Training. We review the application of some of these new algorithms to the terrain correlation measurement processes. The application of these new algorithms improves our support for very large terrain databases, and provides the capability for performing test replications to estimate the sampling error of the tests. With this set of tools, a user can quantitatively assess the degree of correlation between large terrain databases.


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    Title :

    Recent advances on terrain database correlation testing


    Contributors:


    Publication date :

    1998


    Size :

    13 Seiten, 28 Quellen




    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English




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