Discrimination

Award Information
Agency: Department of Defense
Branch: Missile Defense Agency
Contract: HQ0006-10-C-7248
Agency Tracking Number: B083-039-0405
Amount: $1,499,998.00
Phase: Phase II
Program: SBIR
Awards Year: 2010
Solicitation Year: N/A
Solicitation Topic Code: MDA 08-039
Solicitation Number: N/A
Small Business Information
DECISIVE ANALYTICS Corporation
1235 South Clark Street, Suite 400, Arlington, VA, 22202
DUNS: 036593457
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Douglas Ratay
 Senior Engineer
 (703) 682-1514
 douglas.ratay@dac.us
Business Contact
 Kelly McClelland
Title: VP, Administration
Phone: (703) 414-5024
Email: kelly.mcclelland@dac.us
Research Institution
N/A
Abstract
We propose to create a discrimination engine for the Ballistic Missile Defense System (BMDS) based on the concept of manifold learning algorithms. Manifold learning algorithms have come to prominence within the computer vision community as a type of feature extraction algorithm which does not require specific features to be learned a priori. High dimensional sensor data is input to these algorithms which find a lower dimensional representation of the same data, illustrating differences between potential target types. The algorithm can explore regions of the data space for which there are no feature extraction algorithms. We propose to apply these algorithms to high resolution range profiles of target features and embed these results in a novel inference engine to create an on-line discrimination system. Our team consists of staff who have contributed to the development of a prototype system based on these algorithms, as well as radar engineers who can build complex simulated data modeling real objects. In additional Decisive Analytics has a long history of transitioning SBIR technologies to end-users and will work with our partner in this effort, Raytheon, to integrate this discrimination system into an operational radar platform.

* information listed above is at the time of submission.

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