volume | PIER Journals

2004-09-14

Bayesian Optimization Techniques for Antenna Design

Matthew Inman,

Dr. Matthew Inman

Department of Electrical Engineering

University of Mississippi

USA

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John Earwood,

Dr. John Earwood

Department of Electrical Engineering

University of Mississippi

USA

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Atef Elsherbeni,

Professor Atef Elsherbeni

Electrical Engineering Department

Colorado School of Mines

USA

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Charles Smith

Dr. Charles Smith

Department of Electrical Engineering

University of Mississippi

USA

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, Vol. 49, 71-86, 2004

doi:10.2528/PIER04021302 | Google Scholar

Abstract

Optimization and parameter estimation techniques have been employed for many years as a method of improving and exploring designs in numerous areas. As the designs of antennas and antenna arrays become more complex in nature, optimization techniques such as Bayesian estimation or genetic algorithms have become more necessary in the design process. These techniques provide methods for not only the design process, but also for operation simulations such as element failure corrections as well. This paper will deal with Bayesian optimization techniques for antenna and antenna array design as an alternative to other techniques. Through the use of Bayesian inference techniques, probability and information theory can be applied to a design problem to improve the operation within a range of specifications. Examples provided show that how this method allows for the examination of an entire parameter space of a linear array so that the best fitting solutions can be quickly and efficiently examined and improvements can be implemented.

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Matthew Inman, John Earwood, Atef Elsherbeni, and Charles Smith, "Bayesian Optimization Techniques for Antenna Design," , Vol. 49, 71-86, 2004.
doi:10.2528/PIER04021302

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