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Decision Support for Geospatial Intelligence Analysis

Award Information
Agency: Department of Defense
Branch: Air Force
Contract: FA8650-09-M-6973
Agency Tracking Number: F083-020-1672
Amount: $98,949.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: AF083-020
Solicitation Number: 2008.3
Solicitation Year: 2008
Award Year: 2009
Award Start Date (Proposal Award Date): 2009-04-16
Award End Date (Contract End Date): 2010-02-16
Small Business Information
25 Mall Road, Suite 300
Burlington, MA 01803
United States
DUNS: 177274045
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Jeff Harrison
 President and CEO
 (703) 491-9543
Business Contact
 Jeff Harrison
Title: President and CEO
Phone: (703) 491-9543
Research Institution

With improved precision of MTI sensors it is now possible to extract and analyze valuable information through smart algorithms. In particular, identifying Lines of Communication (LOC) is possible using current technologies, providing new GEOINT processes and products. In this SBIR we will identify characterized route topology and geography, linking flows and classifying routes by type.  To do this we will apply techniques we have used effectively in geospatial data conflation, including deriving functional hypotheses based on geometric and inferred topological characteristics of dynamic data and associated geographic features.  Our approach will develop algorithms to provide LOC characterization and fusion from MTI reports. For example, a series of adjacent MTI reports in a chain likely form a route. Combined with MTI velocity and direction vectors, and inference, these reports may provide characterization of the LOC. Our proposal links together two key technologies: an underlying algorithm set accessing geographic features, terrain and route topology that would be modified to extract LOC from MTI streams and a semantic framework which provides the basis for configuring and tuning rules to derive conclusions from geometric, topological and topographic assertions about LOC function.  Our vision for the "end-state" of the Phase 1 research is a credible proof of concept demonstration. BENEFITS: The proposed approach can be integrated as an off-the-shelf toolkit product that wraps the core algorithms and is able to digest common MTI formats while producing common geospatial formats, such as Shapefiles and GML, for full geospatial interoperability. Furthermore we will advance new analysis and awareness front-end tools based on the product, as well as extend the algorithms to multiple sensor types. There is great potential to transition this solution to military application. Initial focus is on the defense, intelligence, command and control markets, where there is a great need for these types of solutions.  In addition, with the growing complexity of border security challenges we see a strong potential for this solution in the homeland security and border surveillance market.

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

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