Optimizations of Patch Antenna Arrays Using Genetic Algorithms Supported by the Multilevel Fast Multipole Algorithm

Date

2014-12-01

Author

Onol, Can
Ergül, Özgür Salih

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We present optimizations of patch antenna arrays using genetic algorithms and highly accurate full-wave solutions of the corresponding radiation problems with the multilevel fast multipole algorithm (MLFMA). Arrays of finite extent are analyzed by using MLFMA, which accounts for all mutual couplings between array elements efficiently and accurately. Using the superposition principle, the number of solutions required for the optimization of an array is reduced to the number of array elements, without resorting to any periodicity and similarity assumptions. Based on numerical experiments, genetic optimizations are improved by considering alternative mutation, crossover, and elitism mechanisms. We show that the developed optimization environment based on genetic algorithms and MLFMA provides efficient and effective optimizations of antenna excitations, which cannot be obtained with array-factor approaches, even for relatively simple arrays with identical elements.

Subject Keywords

Multilevel fast multipole algorithm, Genetic algorithms, Antenna optimizations;, Patch antennas, Antenna arrays

URI

https://hdl.handle.net/11511/54261

Journal

RADIOENGINEERING

Collections

Department of Electrical and Electronics Engineering, Article

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Citation Formats

C. Onol and Ö. S. Ergül, “Optimizations of Patch Antenna Arrays Using Genetic Algorithms Supported by the Multilevel Fast Multipole Algorithm,” RADIOENGINEERING, pp. 1005–1014, 2014, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/54261.