Genetic algorithm optimization of some novel broadband and multiband microstrip antennas

T. G. Spence; D. H. Werner; R. D. Groff

doi:10.1109/aps.2004.1330329

Genetic algorithm optimization of some novel broadband and multiband microstrip antennas

T. G. Spence, D. H. Werner, R. D. Groff

Research output: Contribution to journal › Conference article › peer-review

16 Scopus citations

Abstract

The design of microstrip antennas usually involves specifying the values of several parameters that define its geometry and material characteristics. When there are a large number of parameters, it becomes necessary to use optimization techniques in the design of the antennas in order to maximize their performance. In this paper, we will discuss the design of some novel broadband and multiband microstrip antennas using Genetic Algorithm (GA) optimization techniques. A robust yet efficient optimization strategy that combines Model-Based Parameter Estimation (MBPE) with GA will also be introduced.

Original language	English (US)
Pages (from-to)	4408-4411
Number of pages	4
Journal	IEEE Antennas and Propagation Society, AP-S International Symposium (Digest)
Volume	4
DOIs	https://doi.org/10.1109/aps.2004.1330329
State	Published - 2004
Event	IEEE Antennas and Propagation Society Symposium 2004 Digest held in Conjunction with: USNC/URSI National Radio Science Meeting - Monterey, CA, United States Duration: Jun 20 2004 → Jun 25 2004

All Science Journal Classification (ASJC) codes

Electrical and Electronic Engineering

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10.1109/aps.2004.1330329

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abstract = "The design of microstrip antennas usually involves specifying the values of several parameters that define its geometry and material characteristics. When there are a large number of parameters, it becomes necessary to use optimization techniques in the design of the antennas in order to maximize their performance. In this paper, we will discuss the design of some novel broadband and multiband microstrip antennas using Genetic Algorithm (GA) optimization techniques. A robust yet efficient optimization strategy that combines Model-Based Parameter Estimation (MBPE) with GA will also be introduced.",

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year = "2004",

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AU - Werner, D. H.

AU - Groff, R. D.

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N2 - The design of microstrip antennas usually involves specifying the values of several parameters that define its geometry and material characteristics. When there are a large number of parameters, it becomes necessary to use optimization techniques in the design of the antennas in order to maximize their performance. In this paper, we will discuss the design of some novel broadband and multiband microstrip antennas using Genetic Algorithm (GA) optimization techniques. A robust yet efficient optimization strategy that combines Model-Based Parameter Estimation (MBPE) with GA will also be introduced.

AB - The design of microstrip antennas usually involves specifying the values of several parameters that define its geometry and material characteristics. When there are a large number of parameters, it becomes necessary to use optimization techniques in the design of the antennas in order to maximize their performance. In this paper, we will discuss the design of some novel broadband and multiband microstrip antennas using Genetic Algorithm (GA) optimization techniques. A robust yet efficient optimization strategy that combines Model-Based Parameter Estimation (MBPE) with GA will also be introduced.

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JO - IEEE Antennas and Propagation Society, AP-S International Symposium (Digest)

JF - IEEE Antennas and Propagation Society, AP-S International Symposium (Digest)

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Genetic algorithm optimization of some novel broadband and multiband microstrip antennas

Abstract

All Science Journal Classification (ASJC) codes

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