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EXploitation of Characteristic Information for Threat Evaluation

Award Information
Agency: Department of Defense
Branch: Missile Defense Agency
Contract: HQ0147-13-C-7190
Agency Tracking Number: B12A-002-0032
Amount: $99,982.00
Phase: Phase I
Program: STTR
Solicitation Topic Code: MDA12-T002
Solicitation Number: 2012.A
Solicitation Year: 2012
Award Year: 2013
Award Start Date (Proposal Award Date): 2012-12-10
Award End Date (Contract End Date): 2013-06-13
Small Business Information
100 Wall Street
Princeton, NJ -
United States
DUNS: 096845169
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Jennifer Davis
 Principal Investigator
 (609) 921-3892
Business Contact
 James Lisowski
Title: CEO
Phone: (609) 921-3892
Research Institution
 Georgia Institute of Technology
 Sophia L Herbert-Peterson, Esq.
505 Tenth Street NW
Atlanta, GA 30332-0415
United States

 (404) 385-6705
 Nonprofit College or University

SciTec and Georgia Tech Research Institute (GTRI) propose to develop novel RF/IR kinematic and feature fusion algorithms for incorporation into the Command, Control, Battle Management and Communications (C2BMC) 8.4 track correlation, discrimination, and lethality characterization algorithms that will allow the system to better exploit data from disparate sensors such as the Army Navy/Transportable Radar Surveillance radar (AN/TPY-2) and the Precision Tracking Space System (PTSS). The goal of the proposed work is to determine how to refine the Multiple Hypothesis Correlator, discrimination fusion, and lethality characterization algorithms within C2BMC/GEM to make the best use of data from the radars and from new IR sensors like PTSS, ultimately in support of its primary functions. Residual sensor biases, short-lived, inconsistent covariances, long propagation times between sensor coverage, and detection/tracking of differing subsets of the overall target set render track correlation in the BMDS a challenging problem for any correlator. However, gains (relative to current C2BMC performance) may be realized via use of advanced and robust features in the track correlation, discrimination fusion, and lethality characterization functions.

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

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