Physics Based Missile Trajectory Discrimination Algorithms

Award Information
Agency:
Department of Defense
Branch
Missile Defense Agency
Amount:
$99,946.00
Award Year:
2004
Program:
SBIR
Phase:
Phase I
Contract:
HQ0006-04-C-7004
Award Id:
69531
Agency Tracking Number:
B041-020-0822
Solicitation Year:
n/a
Solicitation Topic Code:
n/a
Solicitation Number:
n/a
Small Business Information
727 Airport Boulevard, Ann Arbor, MI, 48108
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
197187602
Principal Investigator:
Charles Cohen, Ph.D.
Vice President, R&D
(734) 668-2567
ccohen@cybernet.com
Business Contact:
Charles Jacobus, Ph.D.
President and CEO
(734) 668-2567
proposals@cybernet.com
Research Institution:
n/a
Abstract
We believe we have an innovative method for discriminating between real incoming missiles and decoys in a cluttered environment. We have developed a method for taking continuous position information and, using a physical model based on Newton's Laws of Motion and advanced mathematics developed in the field of modern control theory, we have developed algorithms and systems for discriminating between different types of physical motions and activities. The system developed was used for recognizing various human hand and body motions - specifically, gesture recognition. Our goal for the Phase I is to demonstrate that the same physics-based algorithms used for discriminating human gestures and behaviors can also be used to track and identify incoming ballistic missiles. While the motions are quite different, the mathematics behind gesture recognition, as shown in Section d, can work in both areas. Therefore, instead of using this gesture recognition for human-computer interaction, we will leverage our work in this area to create a Target Interception using Gesture Recognition (TIGER) system that will identify, track, and predict the course of incoming missiles and associated decoys. The TIGER system will also discriminate between incoming missiles and decoys, in a manner similar to discriminating between similar human-generated gestures.

* information listed above is at the time of submission.

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