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Progress In Electromagnetics Research
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DESIGN AND OPTIMIZATION OF LOW RCS PATCH ANTENNAS BASED ON A GENETIC ALGORITHM

By X. Zhu, W. Shao, J.-L. Li, and Y.-L. Dong

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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 fit 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 efficiency of the proposed method.

Citation:
X. Zhu, W. Shao, J.-L. Li, and Y.-L. Dong, "Design and Optimization of Low RCS Patch Antennas Based on a Genetic Algorithm," Progress In Electromagnetics Research, Vol. 122, 327-339, 2012.
doi:10.2528/PIER11100703
http://www.jpier.org/PIER/pier.php?paper=11100703

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