Rapid Reprogramming Technologies for Electronic Warfare Training

Award Information
Agency: Department of Defense
Branch: Air Force
Contract: FA8650-13-C-6399
Agency Tracking Number: F103-023-1201
Amount: $744,702.00
Phase: Phase II
Program: SBIR
Awards Year: 2013
Solicitation Year: 2010
Solicitation Topic Code: AF103-023
Solicitation Number: 2010.3
Small Business Information
Battlespace Simulations, Inc
26525 Harmony Hills, San Antonio, TX, -
DUNS: 784877594
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Gary DeYoung
 President
 (210) 857-9672
 gary.deyoung@bssim.com
Business Contact
 Gary DeYoung
Title: President
Phone: (210) 857-9672
Email: gary.deyoung@bssim.com
Research Institution
 Stub
Abstract
ABSTRACT: Warfare is changing at increasingly rapid rate. What was once advanced technology has become simple and inexpensive for our adversaries to obtain. These contemporary truths complicate the U.S. military"s training requirements and result in training solutions that often lag behind the current fight. Current standard simulation technology is typically designed to address a prerequisite set of tactical problems and allows minimal flexibility outside of predetermined constraints. This simulation is focused primarily on recreating what has been observed and perhaps expanded to include some variable conditions also predicated on our observations. The resultant simulation often leaves us mastering the skills of yesterday"s fight and addresses only known threats and observed behaviors in an environment with relatively static adversarial decision making. Future simulation must be as flexible as our adversaries. To this end, BSI proposes the continued development of our Common Cognitive Decision Architecture (C2DA) as a means to help our distributed simulation frameworks rapidly and accurately represent agile, reactive, and adaptable threats. The new Phase II capabilities will give the end-user the tools to perform complex analyses, assessments and calculations, determine available and applicable options, present choices to the user, and inject dynamic behaviors into the target simulation environment. BENEFIT: In Phase II, BSI will leverage and significantly extend the capabilities demonstrated by the BSI Phase I prototype of the Common Cognitive Decision Architecture (C2DA) to empower the non-programmer end-user with the tools to rapidly develop and deploy a highly extensible set of even more powerful and capable rule-based Battlespace Assessments (BAs), Decision Factors (DFs) and Decision Responses (DRs), and control over how those assets are executed, to deliver an exceptional level of dynamic realism to distributed battlespace simulations. The new Phase II capabilities will give the end-user the tools to create and use these BAs, DFs and DRs to perform complex analyses, assessments and calculations, determine available and applicable options, present choices to the user, and inject dynamic behaviors into the target simulation environment. The market for distributed military simulation is vast and increasing as more and more training moves into the simulated realm. Many hundreds of millions of dollars have been spent on DIS-capable simulations, including weapon system trainers (WSTs), full-motion trainers (FMTs), image generators, and a wide variety of SAFs. In short, the market is many orders of magnitude larger than required for BSI to thrive with just a small market share. The first product that will incorporate the C2DA is BSI's Modern Air Combat Environment (MACE). MACE is BSI"s flagship product is the Modern Air Combat Environment (MACE), a DIS-based entity generator and threat environment. Within six months of the initial release of MACE in April of 2011, MACE had been sold to USAF, ANG and USSOCOM units, educational institutions and to companies in the private sector. We believe that a fully developed C2DA will make MACE (and third party CGF/SAFs) even more capable and attractive to our customers, as it externalizes and empowers the end user to dynamically affect entity behaviors, increasing the realism and efficacy of entity interaction in a distributed simulation framework.

* information listed above is at the time of submission.

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