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Linear Ensemble Antennas Resulting from the Optimization of Log Periodic Dipole Arrays Using Genetic Algorithms

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4 Author(s)
Pitzer, T.L. ; Air Force Inst. of Technol., Dayton ; James, A. ; Lamont, G.B. ; Terzuoli, A.J.

Optimization with genetic algorithms (GAs) has become both popular and realistic in the electromagnetic community with the growth in computers and precise electromagnetic computer programs. Intuition is often required for antenna design but GAs can instead define and search a large design space. Using this method results in a non-intuitive and yet very effective antenna architectures. This paper presents an integrated technique to optimize antennas whose basis is Log Periodic Dipole Arrays (LPDA). We use an aggregated fitness function in a multi-objective GA, the NSGA-II, and the optimization software package iSIGHT, along with the Graphical Numerical Electromagnetics Code (GNEC), a method of moments program for antenna design. The results of this design technique compare excellently to Yagi-Uda designs as well as produce acceptable antenna designs based on LPDAs.

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Evolutionary Computation, 2006. CEC 2006. IEEE Congress on

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