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19 May 2005 High fidelity terrain models and geospatial datasets for use in distributed test environments
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Abstract
Distributed testing of a system of systems such is critical to successful development and fielding. Developmental and operational test planning, mission rehearsal, and modeling and simulation of distributed test events requires rapid generation of high-fidelity synthetic environments and geospatial databases that allow efficient transmission and portrayal over network-centric architectures and low-bandwidth communications networks. This paper describes an initiative lead by the U.S. Army Developmental Test Center to rapidly construct digital terrain and surface models using remote sensing data. The authors present methods and techniques used to generate Digital Terrain Elevation Data (DTED) Level 5 or better digital terrain models, surface object databases using Three-Dimensional (3-D) data from airborne Light Detection and Ranging (LIDAR) sensors, and mathematical operations to describe complex geospatial data objects and 3-D topology in highly-compact manners. Currently, units-of-action undergo testing within a defined Common Operating Area (COA) at a training range or proving ground. In coming years, distributed testing, with simulated scenes added to the participating systems, will occur at multiple COAs located at different test facilities. Consistent construction is required for these synthetic environments or scenes for the different facilities. The authors will present trade study results with recommendations for a uniform set of data collection requirements.
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Gerard Snyder, Nick Gorkavyi, David Lashlee, and Max Lorenzo "High fidelity terrain models and geospatial datasets for use in distributed test environments", Proc. SPIE 5805, Enabling Technologies for Simulation Science IX, (19 May 2005); https://doi.org/10.1117/12.603733
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