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PERFORMANCE ENHANCED NAVIGATION USING NEURAL NETWORK TECHNOLOGY (PENANT)

Award Information

Agency:
Department of Defense
Branch:
Air Force
Award ID:
17812
Program Year/Program:
1993 / SBIR
Agency Tracking Number:
17812
Solicitation Year:
N/A
Solicitation Topic Code:
N/A
Solicitation Number:
N/A
Small Business Information
SYNETICS, INC.
555 Edgewater Drive, Third Floor Wakefield, MA 01880
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Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No
 
Phase 2
Fiscal Year: 1993
Title: PERFORMANCE ENHANCED NAVIGATION USING NEURAL NETWORK TECHNOLOGY (PENANT)
Agency / Branch: DOD / USAF
Contract: N/A
Award Amount: $739,084.00
 

Abstract:

SYNETICS PROPOSES A NEW METHOD OF FAULT DETECTION AND IDENTIFICATION (FDI) FOR AIRCRAFT NAVIGATION SYSTEMS, TAKING ADVANTAGE OF BOTH NEURAL NETWORK TECHNOLOGY AND ADVANCED FILTERING TECHNOLOGY. NEURAL NETWORKS OFFER A GREAT DEAL OF PROMISE IN THE GENERAL AREA OF FAULT DETECTION, SINCE THEIR HIGHLY PARALELLIZED STRUCTURE AVOIDS MOST OF THE COMPUTATIONAL DIFFICULTIES ASSOCIATED WITH A TIME-TAGGED FAULT TREE. IN PARTICULAR, RECENT WORK INDICATES THAT THE MULTI-LAYER PERCEPTRON ARCHITECTURE CAN GIVE GOOD FDI PERFORMANCE FOR SOME APPLICATIONS. IN ORDER TO TAKE ADVANTAGE OF NEURAL NETS FOR THE AIRCRAT FDI APPLICATION, IT IS NECESSARY TO FIRST COMPENSATE FOR THE MISSION -DEPENDENT, TIME-VARYING, NON-STATIONARY NATURE OF TYPICAL NAVIGATION ERROR PROCESSES. ALSO, IT IS NECESSARY TO CREATE NEURAL NET INPUTS OVER A LONG ENOUGH TIME HORIZON TO SUCCESSFULLY DIAGNOSE FAULTS, WHILE PRESERVING THE ABILITY TO ELIMINATE THE FAULTY INFORMATION. SYNETICS PROPOSES TO ACCOMPLISH THIS BY PRE-FILTERING THE SENSOR DATA THROUGH A SYNTHETIC MEASUREMENT GENERATOR, BASED ON SYNETICS NET INFORMATION APPROACH (NIA) DISTRIBUTED KALMAN FILTER ALGORITHM. PHASE I WILL INCLUDE ACTUAL TRAINING AND TESTING OF A PROTOTYPE HYBRID NEURAL NET/SMG FOR A REDUCED-ORDER FDI PROBLEM.

Principal Investigator:

Barry Griffiths
6172459090

Business Contact:

Small Business Information at Submission:

Synetics Corp
540 Edgewater Drive Wakefield, MA 01880

EIN/Tax ID:
DUNS: N/A
Number of Employees:
Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No