Target Tracking and Classification System (TTCS)

Award Information
Agency:
Department of Defense
Branch
Navy
Amount:
$69,999.00
Award Year:
2003
Program:
SBIR
Phase:
Phase I
Contract:
N00039-03-C-0089
Award Id:
65053
Agency Tracking Number:
N031-0536
Solicitation Year:
n/a
Solicitation Topic Code:
n/a
Solicitation Number:
n/a
Small Business Information
40 Lloyd Avenue, Suite 200, Malvern, PA, 19355
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
075485425
Principal Investigator:
W. ReynoldsMonach
Vice President
(757) 727-7700
reynolds@va.wagner.com
Business Contact:
W. ReynoldsMonach
Vice President
(757) 727-7700
reynolds@va.wagner.com
Research Institute:
n/a
Abstract
Daniel H. Wagner Associates, Inc. will develop a Target Tracking and Classification System (TTCS) for fusing all available data using Bayesian inferential reasoning, multiple hypothesis association, and non-Gaussian tracking techniques. In Phase I of thisproject we will show how such a system for processing data from large numbers of diverse acoustic receivers (operating in both passive and multi-static active modes), and ISR sensors can be developed, and demonstrate its feasibility and effectiveness usingdemonstration software and simulated (or real-world) data. TTCS will use its fused output to produce an accurate and complete Situation Awareness (SA) picture, easily used and interpreted at all command levels, that will include estimates of the past,current, and future locations of targets of interest and estimates concerning their classification. Such a data fusion capability is especially important in highly cluttered littoral areas, where contact on the targets, even with a large number ofsensors, will be intermittent. In addition, we will utilize existing Wagner Associates non-Gaussian resource optimization algorithms to optimize the placement of fixed acoustic sensors, at no additional cost to the government, taking into account areas ofexpected ISR coverage and possible threat courses of action (COAs). The prototype TTCS will allow us to demonstrate how powerful Bayesian inferential reasoning, multiple-hypothesis, and non-Gaussian data fusion techniques can significantly improve theability of United States forces to conduct ASW, SUW, and mine-laying detection missions. Improved data fusion technologies such as these are particularly necessary at a time when the United States is facing a sophisticated threat in difficult littoralenvironments, such as the Middle East and Korea, with reduced resources.

* information listed above is at the time of submission.

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