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Densely-Packed Target Data Fusion for Naval Mission-level Simulation Systems

Award Information
Agency: Department of Defense
Branch: Navy
Contract: N66001-10-M-5100
Agency Tracking Number: N101-101-0850
Amount: $69,995.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: N101-101
Solicitation Number: 2010.1
Timeline
Solicitation Year: 2010
Award Year: 2010
Award Start Date (Proposal Award Date): 2010-09-09
Award End Date (Contract End Date): 2011-03-09
Small Business Information
14585 Avion Pwy Suite 200
Chantilly, VA 20151
United States
DUNS: 140785929
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Tushar Tank
 Lead Engineer
 (919) 956-5333
 tushar.tank@3phoenix.net
Business Contact
 Joseph Liverman
Title: Principal
Phone: (703) 956-6480
Email: andy.liverman@3phoenix.net
Research Institution
N/A
Abstract

We propose a principled data fusion framework that is appropriate for an adaptive classifier implemented with supervised and multi-task learning. The detection and data fusion (DDF) engine will incorporate a novel Bayes-optimal multiple target tracking system. We will investigate several different metrics of the utility of data fusion in addressing strategic and tactical course of actions. We will perform testing on measured data to help define which is the most appropriate for Navy multi-sensor missions. In addition, we will develop new techniques for feature adaptation and selection based upon current operational scenarios within the battle space.

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

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