Innovative Signature Exploitation for Long Range Object Discrimination

Award Information
Agency:
Department of Defense
Branch
Missile Defense Agency
Amount:
$99,945.00
Award Year:
2012
Program:
SBIR
Phase:
Phase I
Contract:
HQ0147-12-C-7897
Agency Tracking Number:
B112-010-0161
Solicitation Year:
2011
Solicitation Topic Code:
MDA11-010
Solicitation Number:
2011.2
Small Business Information
Technology Service Corporation
3415 S. Sepulveda Blvd, Suite 800, Los Angeles, CA, -
Hubzone Owned:
N
Socially and Economically Disadvantaged:
N
Woman Owned:
N
Duns:
053885604
Principal Investigator:
Michael Thomas
Senior Program Manager
(301) 576-2384
michael.thomas@tsc.com
Business Contact:
David Schubert
VP, WA Operations
(301) 576-2342
david.schubert@tsc.com
Research Institution:
Stub




Abstract
Technology Service Corporation proposes an approach to placing object discrimination on firm foundations in a systems theory and mathematical framework. Using System Identification concepts, we establish the relationships among threat object characteristics and behaviors; rotational motion features, and sensor observations. The systems framework defines metrics and disciplined trade space in which the chief measures of effectiveness are bias, variance, complexity and uncertainty. Complexity has a direct influence on performance. The mathematical formalism also provides for a rigorous accounting of assumptions and usage of a priori information. In Phase I, the theory will be further developed from the preliminary foundations described in this proposal and signature-derived body rotational motion features will be demonstrated using single sensor data. In a proposed Phase I Option, the theory will be applied to investigating body rotation features that exploit multiple sensors. The product of the Phase I research and development will be a detailed report on the system theory framework design, and the evaluation of discrimination performance characteristics. The method benefits C2BMC by characterizing a disciplined trade space, providing metrics that are linked to a theoretical foundation, and offering a path to unify discrimination approaches and assumptions across diverse sensors and other elements.

* information listed above is at the time of submission.

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