Bayesian Network of Support Vector Machines for Robust Threat Identification

Award Information
Agency:
Department of Defense
Branch
Missile Defense Agency
Amount:
$69,997.00
Award Year:
2003
Program:
SBIR
Phase:
Phase I
Contract:
HQ00603C0080
Agency Tracking Number:
031-1117
Solicitation Year:
n/a
Solicitation Topic Code:
n/a
Solicitation Number:
n/a
Small Business Information
EAST WEST ENTERPRISES, INC.
524 JORDAN LANE, HUNTSVILLE, AL, 35805
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
n/a
Principal Investigator:
Paul Cox
Senior Scientist
(256) 534-4782
rama@ewe2000.com
Business Contact:
Ramarao Inguva
President
(256) 534-4782
rama@ewe2000.com
Research Institution:
n/a
Abstract
For any real world pattern classification system (detection, identification, and tracking), there is an inherent problem of optimizing the algorithm's performance for a wide range of scenarios. This is due to a large dynamic range of variables (solarloading, solar reflectance, atmospherics, background, target condition, countermeasures) which will impact the target's feature set. The variability of the feature set is very complex and will depend on time of day, local environmental conditions,previous weather conditions, signature reduction techniques to name a few. East West Enterprises Inc. proposes a novel approach for an adaptive fusion/discrimination algorithm architecture which integrates Bayesian Networks and Support Vector Machines(SVM). SVMs have been used for a variety of applications including detection, classification/recognition/identification, regression and density estimation. In many applications, the SVM has been shown to have superior performance over classicalstatistical and neural network algorithms. The structure of the SVMs incorporates the training sample size, number of features, and desired performance in order to give optimal generalization performance. A fusion architecture is proposed based onintegrating a network of SVM classifiers a Bayesian Network to allow for the adaptive processing/fusion of data from multiple sensors. High fidelity fusion algorithms. These will provide great benefit to military and commercial applications involvingtarget detection, identification, tarcking and discrimination. Potential benefits include MDA/GMD/THAAD, military reconnaisance, surveillance and site monitoring. Commercial applications include homeland defense, medical, and industrial inspection

* information listed above is at the time of submission.

Agency Micro-sites


SBA logo

Department of Agriculture logo

Department of Commerce logo

Department of Defense logo

Department of Education logo

Department of Energy logo

Department of Health and Human Services logo

Department of Homeland Security logo

Department of Transportation logo

Enviromental Protection Agency logo

National Aeronautics and Space Administration logo

National Science Foundation logo
US Flag An Official Website of the United States Government