Predictive Model for Imaging Underwater Objects through the Air-Sea Interface

Award Information
Agency:
Department of Defense
Branch
n/a
Amount:
$79,920.00
Award Year:
2013
Program:
SBIR
Phase:
Phase I
Contract:
N00014-13-M-0028
Agency Tracking Number:
N122-141-0782
Solicitation Year:
2012
Solicitation Topic Code:
N122-141
Solicitation Number:
2012.2
Small Business Information
Arete Associates
P.O. Box 2607, Winnetka, CA, -
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
082191198
Principal Investigator:
Bradley Walls
Program Manager
(520) 770-8629
bwalls@arete.com
Business Contact:
David Kane
Executive Vice President
(520) 571-8660
contracts@arete.com
Research Institution:
Stub




Abstract
The science of Mine Countermeasures (MCM) is a challenging and multidimensional problem that involves the detection and classification of sea mines both underwater and at the surface. In recent years, MCM has undergone dramatic advances in detector technology, computational power, and algorithmic maturity giving the potential for a"never-before-seen"capability to detect and classify sea mines. Essential to the continuing success for application of EO systems to the MCM problem is the ability to model targets in the marine environment to gain a better the understanding of target phenomenology. This will pave the way to better EO sensor designs and more robust detection and classification algorithms. Making high fidelity models and realistic simulations possible is the fundamental theory derived from numerous investigations into the details of radiative transfer within the ocean environment. Jerlov (1979), Gordo (1988), and Mobley (1993). However, McLean and Freeman (1996) extended these simple models to include wave effects of the ocean surface. Leveraging this research and well validated propagation models, Arete Associates will develop a robust, high-fidelity electro-optical radiative transfer model to predict the time-varying visibility of submerged objects.

* information listed above is at the time of submission.

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