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Network Enhanced Automatic Target Recognition

Award Information
Agency: Department of Defense
Branch: Navy
Contract: N00014-07-M-0438
Agency Tracking Number: N074-024-0429
Amount: $69,995.00
Phase: Phase I
Program: STTR
Solicitation Topic Code: N07-T024
Solicitation Number: N/A
Solicitation Year: 2007
Award Year: 2007
Award Start Date (Proposal Award Date): 2007-07-20
Award End Date (Contract End Date): 2008-05-20
Small Business Information
1230 Arizona Sun Grove
Colorado Springs, CO 80909
United States
DUNS: 050873459
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 David Ward
 (719) 447-8757
Business Contact
 David Ward
Title: President
Phone: (719) 447-8757
Research Institution
 Magaret A Bacon
1420 Austin Bluffs Parkway
Colorado Springs, CO 80933
United States

 (719) 262-3436
 Nonprofit College or University

Networked Enhanced Automated Target Recognition (NEATR), is an important problem in modern network centric operations. This Phase I effort focuses on fusion in an embedded system with reasonable Size Weight and Power (SWAP). The proposed multi-layer approach provides novel detection and re-identification layers, target tracking and enhanced PCA-based recognition. The proposal presents a unique new approach, P+PCA simultaneously estimating, in a distributed multi-hypothesis manner, target position, pose and coefficients in a parametric PCA-eigenspace. Estimation of position and pose are traditional target tracking fusion issues, we integrate them with the estimation the parameters and uncertainties needed to improve the distributed ATR performance from reduced resolution data. The approach is designed for low-bandwidth communications and does not transmit the imagery for fusion. The effort builds on the team's decade of experience delivering on DOD-funded surveillance and recognition R&D efforts. This Phase I will develop a functioning FPGA-based prototype to address key feasibility questions, new algorithms tested on real data and will develop and analyzes the overall architecture for distributed recognition.

* Information listed above is at the time of submission. *

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