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Efficient Sensor Management for Optimal Multi-Task Performance (ES-MaTe)

Award Information

Agency:
Department of Defense
Branch:
N/A
Award ID:
Program Year/Program:
2011 / SBIR
Agency Tracking Number:
B103-002-0566
Solicitation Year:
2010
Solicitation Topic Code:
MDA10-002
Solicitation Number:
2010.3
Small Business Information
Knowledge Based Systems, Inc.
1408 University Drive East College Station, TX 77840-2335
View profile »
Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No
 
Phase 1
Fiscal Year: 2011
Title: Efficient Sensor Management for Optimal Multi-Task Performance (ES-MaTe)
Agency: DOD
Contract: HQ0147-11-C-7556
Award Amount: $100,000.00
 

Abstract:

Knowledge Based Systems, Inc. (KBSI) proposes to investigate innovative methodologies and algorithms for Efficient Sensor Management for Optimal Multi-Task Performance (ES-MaTe), The goal of the proposed research is to investigate an efficient sensor resource management method for sensor scheduling specific to tasks required by a missile defense system. The Ballistic Missile Defense System uses multiple disparate and spatially separated sensors for multiple simultaneous tasks such as target search, detection, acquisition, discrimination, target tracking. Each of these tasks consists of minimization of uncertainty in estimation of some underlying stochastic process. However, sharing of resources with other tasks results in some degradation of the estimation performance. ES-MaTe will develop a constraint optimization technology for non-myopic multi-sensor scheduling that will ensure some level of minimum performance for each task by imposing performance constraints based on uncertainty measurements, while maximizing the total information gain. A feature of the optimization problem includes the imposition of several types of task specific sensor utilization constraints. The optimal non-myopic sensor scheduling requires dynamic programming that becomes unpractical due to complexity arising from combinatorial explosion. Approximate dynamic programming techniques will be investigated for practical implementation.

Principal Investigator:

Ajay Verma
Research Scientist
(979) 260-5274
averma@kbsi.com

Business Contact:

Donielle Mayer
Business Operations Mgr.
(979) 260-5274
dmayer@kbsi.com
Small Business Information at Submission:

Knowledge Based Systems, Inc.
1408 University Drive East College Station, TX -

EIN/Tax ID: 742505334
DUNS: N/A
Number of Employees:
Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No