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A Game Theoretic Approach for Threat Prediction and Situation Awareness

Award Information

Agency:
Department of Defense
Branch:
Navy
Award ID:
75421
Program Year/Program:
2005 / STTR
Agency Tracking Number:
N054-019-0310
Solicitation Year:
N/A
Solicitation Topic Code:
N/A
Solicitation Number:
N/A
Small Business Information
Intelligent Automation, Inc.
15400 Calhoun Drive suite 400 Rockville, MD 20855-2735
View profile »
Woman-Owned: Yes
Minority-Owned: No
HUBZone-Owned: No
 
Phase 1
Fiscal Year: 2005
Title: A Game Theoretic Approach for Threat Prediction and Situation Awareness
Agency / Branch: DOD / NAVY
Contract: N00014-05-M-0205
Award Amount: $70,000.00
 

Abstract:

Intelligent Automation, Inc. (IAI), and its sub-contactor, Professor Carl G. Looney from University of Nevada propose a highly innovative approach for Level 2+ information fusion using hybrid data fusion with adversarial Markov game, named a Game Theoretic Approach for Threat Prediction and Situation Awareness. The primary goal is to investigate and demonstrate the effectiveness of Markov game theory and the advanced knowledge infrastructures for Level 2+ information fusion, such as Situation Assessment (Refinement) and Threat Assessment (Refinement) and so on, therefore improve the capabilities of battlefield situation awareness. To achieve this goal, first, a hybrid data fusion approach is proposed to apply in Situation Refinement to perform spatial and temporal processing on tracks produced by Level 1 multi-sensor, multi-target track fusion, supplemented with intelligence information from both structured data sources such as databases and unstructured data sources such as ontology-based documents. Second, ontology-based information representation is proposed for building a Virtual Battlespace with less computational complexity in Level 2 fusion. Third, an adversarial Markov game framework is proposed for Threat Refinement to drive existing and newly formulated models of threat behavior with factlets derived from Situation Refinement to support the determination of possible enemy courses of actions.

Principal Investigator:

Genshe Chen
Research Electrical Engineer
3012945218
gchen@i-a-i.com

Business Contact:

Mark James
Contracts and Proposals Manager
3012945221
mjames@i-a-i.com
Small Business Information at Submission:

Intelligent Automation, Inc.
15400 Calhoun Drive, Suite 400 Rockville, MD 20855

EIN/Tax ID: 521497192
DUNS: N/A
Number of Employees:
Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No
Research Institution Information:
UNIV. OF NEVADA
College of Engineering
Reno, NV 89554
Contact: Carl G. Looney
Contact Phone: (775) 784-6974
RI Type: Nonprofit college or university