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Automated Generation of Electronic Warfare Libraries

Award Information

Agency:
Department of Defense
Branch:
N/A
Award ID:
Program Year/Program:
2013 / SBIR
Agency Tracking Number:
N131-036-0948
Solicitation Year:
2013
Solicitation Topic Code:
N131-036
Solicitation Number:
2013.1
Small Business Information
Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No
 
Phase 1
Fiscal Year: 2013
Title: Automated Generation of Electronic Warfare Libraries
Agency: DOD
Contract: N00024-13-P-4583
Award Amount: $79,996.00
 

Abstract:

Metrological differences between tactical sensors result in a wide range of accuracy, completeness, and correctness of features used for object classification. Thus, it is typical practice for Subject Matter Experts (SMEs) to develop the required reference libraries so that they are tailored to each tactical sensor type and, in some cases, sensing environments. The process of developing this tailored library is often called"coloring"the reference library. The SMEs objective is to optimize the classification performance (w.r.t. some metric(s)) using a feature-based classifier. The proposed Hierarchical Emitter Library Optimization (HELO) technology mimics the coloring process in order to generate an Emitter Library that optimizes the classifier performance while avoiding the need for a labor-intensive manual process that requires SME knowledge. HELO employs a general Hierarchical Evolutionary Programming (H-EP) based upon the Genetic Programming (GP) optimization paradigm to achieve this optimization. This approach provides a computationally scalable process that rigorously quantifies the performance of the classification algorithms without knowledge of its algorithms. Using the performance assessment of the classifier, a large set of potential emitter libraries (population) is iteratively refined (evolved) until an optimal (or sufficiently good) emitter library is generated. The solution is hierarchical because the evolution of the population is achieved jointly in two stages: (1) evolution of the coloring functions to generate a parameter library for a particular parameter type and (2) evolution of the set of parameters used by the classifier.

Principal Investigator:

William Farrell
Director of Information F
(410) 381-9780
jim.farrell@lakota-tsi.com

Business Contact:

J. Pence
President
(410) 381-9780
rob.pence@lakota-tsi.com
Small Business Information at Submission:

Lakota Technical Solutions, Inc.
PO Box 2309 Columbia, MD -

EIN/Tax ID: 522073737
DUNS: N/A
Number of Employees:
Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No