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Distributed Synthetic Environment Correlation Assessment Architecture and Metrics

Award Information
Agency: Department of Defense
Branch: Navy
Contract: N68335-14-C-0207
Agency Tracking Number: N141-006-0262
Amount: $79,997.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: N141-006
Solicitation Number: 2014.1
Timeline
Solicitation Year: 2014
Award Year: 2014
Award Start Date (Proposal Award Date): 2014-05-13
Award End Date (Contract End Date): 2014-11-10
Small Business Information
1002 Partin Court
Oviedo, FL 32765-5922
United States
DUNS: 60-870-58
HUBZone Owned: No
Woman Owned: Yes
Socially and Economically Disadvantaged: No
Principal Investigator
 Mark Faulk
 Technical Director
 (407) 496-0515
 mfaulk@cssflorida.net
Business Contact
 Michael Puhlmann
Title: Vice President of Operati
Phone: (407) 687-7594
Email: mpuhlmann@cssflorida.net
Research Institution
 Stub
Abstract

To support the growing need to train as you fight, there is a corresponding need to interoperate between previously segregated Navy and Marine Corps flight simulators. To achieve this interoperability, there must me a rapid, cost effective way to measure and manage the correlation between terrain databases, 3D models, and sensors. Cornerstone proposes to establish a consistent set of metrics and an open, extendable tool-set architecture to measure the degree of correlation and present that analysis in easy to consume formats. The architecture will support tying the metrics and analysis findings to potential training impacts and provide for weighting of analysis parameters based on the specific training objectives and needs of each simulator. The architecture will be extendable through a plugin capability that supports integration of third party developers. We will define the architectural requirements and quality attribute goals through use case and domain requirements analysis to ensure it supports the true needs of the user community. The architecture will support on-site data collection and analysis as well as engineering lab longer term trend and prevention analysis. It will also support exporting analysis data for use by external research teams.

* Information listed above is at the time of submission. *

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