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Intelligent RF-IR Data Fusion using Artificial Intelligence Techniques

Award Information
Agency: Department of Defense
Branch: Missile Defense Agency
Contract: HQ0147-13-C-7192
Agency Tracking Number: B12A-002-0029
Amount: $99,992.00
Phase: Phase I
Program: STTR
Solicitation Topic Code: MDA12-T002
Solicitation Number: 2012.A
Solicitation Year: 2012
Award Year: 2013
Award Start Date (Proposal Award Date): 2012-10-18
Award End Date (Contract End Date): 2013-04-18
Small Business Information
951 Mariners Island Blvd., STE 360
San Mateo, CA -
United States
DUNS: 608176715
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Richard Stottler
 Principal Investigator
 (650) 931-2700
Business Contact
 Carolyn Maxwell
Title: Contracts Manager
Phone: (650) 931-2700
Research Institution
 U. of Dayton Research Institute
 Linda Young
300 College Park
Dayton, OH 45469-0104
United States

 (937) 229-2919
 Nonprofit College or University

There may be no more important mission for the US military than protection from ballistic missile attack. For any configuration of sensors, it is therefore extremely important to make the most of the collected sensor data. Specifically, this proposal describes how this objective can be accomplished by using artificial intelligence techniques to implement human-quality reasoning on object features extracted from sensor data. The ultimate goal of this proposed effort is to better utilize disparate sensor data to perform better correlations and lethality assessments for ballistic missile defense targets in the midcourse phase through the development of a sensor data fusion system. By performing human quality reasoning, the proposed system can perform superiorly to other systems utilizing the same sensor data. The goals of the Phase I research are to understand the missile defense radar-IR sensor fusion domain, elaborate the heuristics, algorithms and techniques for multi-sensor data fusion correlation and classification, analyze them as to their feasibility in several dimensions, collect actual X-band and IR sensor data in Phase I, further prove the feasibility of the techniques through prototype development and performance testing with real data, and develop the Phase II system design.

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

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