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Discrimination

Award Information

Agency:
Department of Defense
Branch:
Missile Defense Agency
Award ID:
91599
Program Year/Program:
2009 / SBIR
Agency Tracking Number:
B083-039-0405
Solicitation Year:
N/A
Solicitation Topic Code:
N/A
Solicitation Number:
N/A
Small Business Information
DECISIVE ANALYTICS Corporation
1235 South Clark Street Suite 400 Arlington, VA 22202-
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Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No
 
Phase 1
Fiscal Year: 2009
Title: Discrimination
Agency / Branch: DOD / MDA
Contract: HQ0006-09-C-7163
Award Amount: $99,999.00
 

Abstract:

The performance of the Ballistic Missile Defense System depends on a number of factors; one of the most important is the ability to accurately and efficiently discriminate between threats (reentry vehicles) and non-threats (decoys). The DECISIVE ANALYTICS Corporation (DAC) team proposes to develop a discrimination system based on a novel machine learning algorithm called Maximum Variance Unfolding (MVU). The MVU algorithm combines the attributes of data compression and feature extraction, effectively learns nonlinear transformations such as changes in object morphology and dynamic object motion, and can be cast in the form of a semi-definite program which guarantees an optimal solution to the problem. We will illustrate the proficiency of our approach by learning high fidelity, high resolution radar signatures of a dynamic target model and testing the discrimination system on scenarios that confound the current Discrimination Fusion Engine (DFE). Phase II of this project will focus on integrating our discrimination system with our novel dynamic, hybrid Bayesian network model for combining tracking and discrimination.

Principal Investigator:

David Fiske
Senior Engineer
7034145036
david.fiske@dac.us

Business Contact:

Kelly McClelland
Director, Corporate Business Office
7034145024
kelly.mcclelland@dac.us
Small Business Information at Submission:

DECISIVE ANALYTICS CORP.
1235 South Clark Street Suite 400 Arlington, VA 22202

EIN/Tax ID: 541785147
DUNS: N/A
Number of Employees:
Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No