TECHNOLOGY AREAS: Air Platform, Information Systems, Sensors

ACQUISITION PROGRAM: Joint Strike Fighter

OBJECTIVE: Develop abstract methods of defining mixed topographical features on rural and urban terrain (e.g., adjoining man-made and natural objects having complex geometrical solutions, such as caves, highway interchanges with multiple level ramps, walkways between high-rise towers etc.). Develop optimized real-time rendering algorithms that allow dynamic interaction with the above complex features in a training simulation environment.

DESCRIPTION: Current standards used for representing terrain digital elevation models do not provide for the description of topographical features such as tunnels, caves/bunkers, overhangs, multi-level highways/interchanges, and other unique aspects of strategic rural environments and urban infrastructures. Abstract methods for defining and rendering these topographical features are desired, to allow for embedding realistic targets and simulated lasing of those targets, as well as ability to accommodate temporal/diurnal changes to the topography.

The developed definitions should facilitate advanced rendering techniques for producing unaided visual, Night Vision Goggles (NVG), Infra-Red/Forward-Looking Infra-Red (IR/FLIR), and radar scenes, such as using multi-pass methods for lighting, geometry, shading, and atmospheric and special effects. The developed capability should also facilitate use of the wide array of United States Geological Survey (USGS) products, and of urban planning data sets/imagery from local, state, and federal agencies. Support for multiple database schemas is desired, allowing for database reuse without requiring custom format conversions. A goal is to achieve compatibility with (or extension of) existing military database re-use initiatives, such as Navy Portable Source Initiative (NPSI), Master Database (MSB), Common Database (CDB), and Synthetic Environment Core (SE Core).

For the purposes of training: lasing of targets, damage assessment after strikes, supporting complex interaction of simulated weapon platforms with targets of interest, and for training situational awareness, battle-state assessment, and low level navigation.

PHASE I: Define and determine the feasibility of innovative concepts for simulating dynamic real-time interaction with complex terrain and topography features within a seamless simulation environment, and provide proof of concept.

PHASE II: Develop, integrate, demonstrate and evaluate a prototype that incorporates real-world data and imagery from a wide-range of sources (commercial, municipal, government) and supports a variety of visual/sensor scenes.

PHASE III: Commercialize and transition the system and apply to a complex training simulator.

PRIVATE SECTOR COMMERCIAL POTENTIAL/DUAL-USE APPLICATIONS: Commercial applications range from environmental studies to emergency (natural disaster and/or terrorism) planning, construction management and training. Both military and nonmilitary sectors require more sophisticated models using the wealth of data that is now being generated from commercial enterprises and by local, state, and federal governments. The depiction of dynamic terrain is particularly important in the visualization of construction operations as well as in combat because terrain is seen and manipulated at close range.

REFERENCES:
1. Kamat, V.R., Martinez, J.C. (2003). Automated Generation of Large-Scale Dynamic Terrain in 3D Animation of Simulated Construction Processes. CONVR Virginia Tech, September 24th � 26th. http://pathfinder.engin.umich.edu/documents/Kamat&Martinez.CONVR2003.ResearchPaper.pdf.

2. Turner, D.P., Ollinger, S.V., Kimball, J.S. (2004). Integrating Remote Sensing and Ecosystem Process Models for Landscape- to Regional-Scale Analysis of the Carbon Cycle. BioScience June 2004 / Vol. 54 No. 6: 573-584. http://wwwdata.forestry.oregonstate.edu/larse/pubs/turner_bioscience.pdf.

3. Eyers R.D; Mills, J. P. (2005). Subsidence Detection Using Integrated Multi Temporal Airborne Imagery. The International Archives of the Photogrammetry, Remote Sensing and
Spatial Information Sciences, Vol. 34, Part XXX. http://www.isprs.org/istanbul2004/comm7/papers/140.pdf.

KEYWORDS: Simulation Databases; Training Systems; Simulation Training; Feature/Target Recognition; Synthetic Environment Databases; 3-D Modeling

** TOPIC AUTHOR (TPOC) **

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