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

Award Information
Agency: Department of Defense
Branch: Navy
Contract: N/A
Agency Tracking Number: 18207
Amount: $465,630.00
Phase: Phase II
Program: SBIR
Awards Year: 1993
Solicitation Year: N/A
Solicitation Topic Code: N/A
Solicitation Number: N/A
Small Business Information
6811 Kenilworth Avenue, Riverdale, MD, 20737
DUNS: N/A
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Dr. Srinivasan Raghavan
 (301) 927-3223
Business Contact
Phone: () -
Research Institution
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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