Seamlessly Unified Reasoning Under Uncertainty for Missile Defense Architectures

Award Information
Agency:
Department of Defense
Branch:
Missile Defense Agency
Amount:
$99,992.00
Award Year:
2005
Program:
SBIR
Phase:
Phase I
Contract:
HQ0006-05-C-7136
Agency Tracking Number:
044-1116
Solicitation Year:
2004
Solicitation Topic Code:
MDA04-158
Solicitation Number:
2004.4
Small Business Information
SCIENTIFIC SYSTEMS CO., INC.
500 West Cummings Park - Ste 3000, Woburn, MA, 01801
Hubzone Owned:
N
Socially and Economically Disadvantaged:
Y
Woman Owned:
N
Duns:
859244204
Principal Investigator
 Adel El-Fallah
 Associate Group Leader
 (781) 933-5355
 adel@ssci.com
Business Contact
 Raman Mehra
Title: President
Phone: (781) 933-5355
Email: rkm@ssci.com
Research Institution
N/A
Abstract
Scientific Systems Company Inc. (SSCI) of Woburn MA and its subcontractor Lockheed Martin Tactical Systems (LMTS) of Eagan MN propose a radically new approach to expert systems theory that will greatly facilitate the effective design of BMD decision architectures. We will show that, as most commonly employed in the problem domain of interest---fusing information to obtain estimates of target states and estimates of uncertainty in those states---evidence-fusion using Dempster-Shafer, fuzzy logic, and rule-based can be rigorously subsumed within the Bayesian theory. Thus fusion of ambiguous measurements using Dempster's rule of combination '*' or Zadeh's conjunction operator '^' produce exactly the same answer as fusion using Bayes' rule. Rules---including second-order rules---can be processed in a recursive Bayes filter as just another kind of data. From a BMD decision architecture point of view, the following are immediate consequences: (1) the relationships between, and relative strengths and weaknesses of, the different expert systems approaches can be directly compared; (2) algorithm and architecture design can become more systematic and integrated; and (3) it is no longer necessary to "re-invent the wheel" when using fuzzy logic, Dempster-Shafer, and rule-based methods since we can draw from a huge "toolbox" of established probabilistic concepts and techniques. The approach can be rigorously extended to multisource-multitarget detection, tracking, and identification. The project team includes Dr. Ronald Mahler of Lockheed Martin. Lockheed Martin will provide both technical and commercialization support in the application of expert systems approaches to multisource-multitarget tracking.

* information listed above is at the time of submission.

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