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DYNAMICALLY PROGRAMMABLE AND ADAPTIVE MULTI-BAND COMPRESSIVE IMAGING SYSTEM

Award Information
Agency: Department of Defense
Branch: Army
Contract: W911NF-13-C-0066
Agency Tracking Number: A2-5020
Amount: $416,990.00
Phase: Phase II
Program: STTR
Solicitation Topic Code: A11a-T007
Solicitation Number: 2011.
Timeline
Solicitation Year: 2011
Award Year: 2013
Award Start Date (Proposal Award Date): 2013-05-01
Award End Date (Contract End Date): 2014-05-01
Small Business Information
2310 University Way, Bldg 4-4
Bozeman, MT -
United States
DUNS: 788293244
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Randy Reibel
 Vice President
 (406) 585-2774
 reibel@bridgerphotonics.com
Business Contact
 Sandra Reibel
Title: Financial Manager
Phone: (406) 585-2774
Email: sandy@bridgerphotonics.com
Research Institution
 University of Arizona
 Amit Ashok
 
1639 East University Blvd. Meinel Building
Tucson, AZ 85721-
United States

 (520) 626-4815
 Nonprofit College or University
Abstract

Bridger Photonics, Inc. and the University of Arizona have successfully demonstrated a Phase I dynamically programmable multi-band compressive imaging system. The team demonstrated three key technical concepts that prove the feasibility of this powerful technology: 1. Advanced algorithms were used to develop compressive measurement basis sets for imaging and target classification. The algorithms and basis sets were validated experimentally with imaging hardware and mock battlespace scenes. 2. Hardware was developed to perform compressive sensing in two spectral bands simultaneously. Images up to 64 x 128 were formed with nearly 10x compression and target detection was performed. 3. A dynamically programmable processor was implemented to enable rapid switching between system tasks and adaptive measurements. Based on the positive outcome of these demonstrations, the team has determined a Phase II prototype design to meet the Army"s Phase II goals. The Phase II system will produce 2-megapixel images with 10x compression in four spectral bands. In addition, the system will use advanced algorithms to provide jointly optimized image reconstruction and classification/detection. The team"s proven expertise and experience with compressive sensing algorithms, imaging hardware, and rapid prototyping will enable the development of state-of-the-art compressive sensing algorithms and hardware during the Phase II effort.

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

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