SBIR/STTR Research Award

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

Award identifier 16ca9630fd21b62fe61d39f7335ad342f5a55e0faf555fac3b6c9a19709e9a29Awarding agency Department of Defense · Navy

Award amount

$465,630

Program and phase

SBIR · Phase II

Award year

1993

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Award details

Awarding agency
Department of Defense
Branch
Navy
Recipient company
LNK CORP., INC.
Proposal award date
Not reported
Contract end date
Not reported
UEI
Not reported
Solicitation number
Not reported
Topic code
Not reported

Research 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.

Technology keywords

Not reported

Agency intelligence

Department of Defense

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