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Progress In Electromagnetics Research
Article . 2012 . Peer-reviewed
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DESIGN AND OPTIMIZATION OF LOW RCS PATCH ANTENNAS BASED ON A GENETIC ALGORITHM

Authors: Xinyue Zhu; Wei Shao; Jia-Lin Li; Yu-Liang Dong;

DESIGN AND OPTIMIZATION OF LOW RCS PATCH ANTENNAS BASED ON A GENETIC ALGORITHM

Abstract

In this article, a genetic algorithm (GA) is employed to the design of low radar cross section (RCS) patch antennas. Combined with the high frequency simulation software (HFSS) for antenna simulations, the GA performs the optimization of geometric parameters. In order to reduce the RCS while holding the satisfying radiation performance of antennas, the radiation model and scattering model are respectively calculated. The combination of proportionate selection and elitist model for the selection strategy is used to speed up the convergence of the GA. Two-point crossover is adopted to accelerate the converging speed and results in more flt individuals. Moreover, the whole design procedure is auto-controlled by programming the VBScript in the HFSS. Two examples of low RCS slot antennas are provided to verify the accuracy and e-ciency of the proposed method.

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    influence
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
23
Top 10%
Top 10%
Top 10%
gold