Antenna design by genetic algorithms

Award Information
Agency: Department of Defense
Branch: Navy
Contract: N00014-08-M-0300
Agency Tracking Number: N08A-031-0092
Amount: $69,993.00
Phase: Phase I
Program: STTR
Awards Year: 2008
Solicitation Year: 2008
Solicitation Topic Code: N08-T031
Solicitation Number: 2008.A
Small Business Information
315 S. Allen St., Suite 222, State College, PA, 16801
DUNS: 945483733
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Stephen Fast
 Executive Vice President
 (814) 861-1299
 sfast@remcom.com
Business Contact
 Stephen Fast
Title: Executive Vice President
Phone: (814) 861-1299
Email: sfast@remcom.com
Research Institution
 THE PENNSYLVANIA STATE UNIV.
 Randy Haupt
 ARL Penn State
PO Box 30, N. Atherton Street
State College, PA, 16804
 (814) 865-7299
 Nonprofit college or university
Abstract
In many military and civilian situations, the placement of an antenna is restricted by available space and surrounding structures. Additionally, antenna design engineers are continuously considering various methods that can optimize an antenna design for criteria, e.g. radiation efficiency, directionality, or S parameters. Once the performance criteria are specified, it becomes necessary to find the best solution(s) that satisfy the design constraints. For example, one might try to place an antenna on a vehicle in such a manner as to radiate energy in one direction while causing minimal interference to other antennas nearby. Optimal antenna placement of an antenna on a platform is a challenge to current approaches to electromagnetic modeling and numerical optimization. Genetic algorithms (GAs) and other "global" search algorithms have the advantage of being able to search cost surfaces with many local minima. They can also handle a large number of variables and constraints. Some current limiting factors include the optimization mixed variable types (continuous, discrete, and categorical) and the slow speed of calculating the cost function. This proposal addresses both of these impediments through the use of a very fast and accurate commercial code and a new type of GA called a mixed integer GA.

* Information listed above is at the time of submission. *

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