A Synergic Expert-Neural Network System to Identify Relocatable Targets using Multi-Sensor Fusion

Award Information
Agency:
Department of Defense
Branch
Navy
Amount:
$465,630.00
Award Year:
1993
Program:
SBIR
Phase:
Phase II
Contract:
n/a
Award Id:
18207
Agency Tracking Number:
18207
Solicitation Year:
n/a
Solicitation Topic Code:
n/a
Solicitation Number:
n/a
Small Business Information
6811 Kenilworth Avenue, Riverdale, MD, 20737
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
n/a
Principal Investigator:
Dr. Srinivasan Raghavan
(301) 927-3223
Business Contact:
() -
Research Institute:
n/a
Abstract
The central focus of this proposal is on building an automatic target recognition system for identifyi-ng relocatable targets by integrating information from multiple sensors using a synergistic framework of neural networks and exprt systems. This frairework is ideally suited for 3..ricorporating human expertise of both perceptual and qualitative reasoning processes . From our prior experience in this area (NADC N62269-90-C-0567), we find the key to an efficient solutLon lies in using a composite architecture conbining an e)q.rt system with a hybrid neural subsystem. We propose a th ^ elevel processing system for identi- fying the relocatable targets. Th- first level of %is system addresses issues related to data representa^Lon and registration ljetween sources . The second level achieves feature extraction and parbLal recognition results using neural networks. Die third level consists of a decision maki-ng expert system wLth fuzzy logic reasonlng to achieve a collectLve decision from the multi.ple sources using an object-oriented representaLLon of the target.

* information listed above is at the time of submission.

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