Performance-Based Sensor Resource Management for Missile Defense

Award Information
Agency:
Department of Defense
Branch
Missile Defense Agency
Amount:
$100,000.00
Award Year:
2011
Program:
SBIR
Phase:
Phase I
Contract:
HQ0147-11-C-7617
Agency Tracking Number:
B103-002-0527
Solicitation Year:
2010
Solicitation Topic Code:
MDA10-002
Solicitation Number:
2010.3
Small Business Information
Toyon Research Corp.
CA, Goleta, CA, 93117-3021
Hubzone Owned:
N
Socially and Economically Disadvantaged:
N
Woman Owned:
N
Duns:
054672662
Principal Investigator:
Mark Meloon
Senior Analyst
(805) 968-6787
mmeloon@toyon.com
Business Contact:
Marcella Lindbery
Director of Finance
(805) 968-6787
mlindbery@toyon.com
Research Institution:
Stub




Abstract
Toyon Research Corporation proposes to develop a sensor resource management (SRM) algorithm that generates schedules that assign sensors to specific tasks, chosen to best protect numerous defended areas from multiple raids. We cast the problem of SRM as a combinatorial optimization problem and our algorithm assembles multi-sensor schedules from a set of candidate sensor tasks to minimize an objective function. The formation of candidate takes into account such constraints as availability, accessibility, and measurement capabilities. The objective function combines elements of information theory with measures of site survivability to quantify the mission objective. We solve the optimization problem using a branch-and-bound technique to generate good schedules quickly. This Phase I study will build on work we have performed in the area of SRM for over ten years and develop the extensions and modifications that will make it ideal for the problem of multi-raid, multi-target environments. Specific tasks we will pursue include development of sensor task creators and a suitable objective function, implementation in software, and demonstration of the effectiveness and computational tractability on an example problem. In Phase II we will integrate our software prototype with a sophisticated simulation framework and demonstrate our algorithm against more challenging problems.

* information listed above is at the time of submission.

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