Mover and Alert Detection and Hardware Accelerated Target Tracking using Efficient Resources (MAD-HATTER)

Award Information
Agency:
Department of Defense
Branch:
Navy
Amount:
$149,899.00
Award Year:
2012
Program:
SBIR
Phase:
Phase I
Contract:
N00014-12-M-0179
Agency Tracking Number:
N121-084-0073
Solicitation Year:
2012
Solicitation Topic Code:
N121-084
Solicitation Number:
2012.1
Small Business Information
Charles River Analytics Inc.
625 Mount Auburn Street, Cambridge, MA, -
Hubzone Owned:
N
Socially and Economically Disadvantaged:
N
Woman Owned:
N
Duns:
115243701
Principal Investigator
 Ross Eaton
 Senior Scientist
 (617) 491-3474
 reaton@cra.com
Business Contact
 Mark Felix
Title: Contracts Manager
Phone: (617) 491-3474
Email: mfelix@cra.com
Research Institution
 Stub
Abstract
Small unmanned aircraft systems (UAS) have become a critical part of Intelligence, Surveillance and Reconnaissance (ISR) missions, supplying valuable aerial imagery to ground forces. Unfortunately, operational ISR is compromised by the stringent size, weight, and power constraints of small UASs, which cannot support real-time processing of imagery nor real-time transmission of high resolution video over limited-bandwidth communication links. Therefore, the potentially game-changing combination of high-resolution ISR and tactical-edge availability has not yet materialized. Our proposed solution is an integrated hardware/software system designed to process high-resolution video data at full video-rate onboard a small UAS. The software performs mover detection and feature-aided tracking, such that only narrow-bandwidth results need to be transmitted back to the user. Our solution employs a revolutionary computing hardware architecture offering several orders of magnitude greater efficiency over conventional processors in terms of throughput vs. power consumption. The key innovation is a slightly reduced precision arithmetic logic unit (ALU) built from just a few thousand transistors, instead of the hundreds of thousands used in modern floating point units. Our simulations show that simple parallel architectures based on these extremely small ALUs run applications 10,000 times more efficiently (faster, or lower power) than modern CPUs and 100 times more efficiently than GPUs.

* information listed above is at the time of submission.

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