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Synthesis of Linear Antenna Array Using Genetic Algorithm with Cost Based Roulette Wheel Selection to Maximize Sidelobe Level Reduction


Affiliations
1 Department of Electronics and Communication Engineering, HolyCross Engineering College, Anna University of Technology, Tirunelveli, Tamil Nadu, India
2 Department of Electronics and Communication Engineering, Thiagarajar College of Engineering, Madurai, Tamil Nadu, India
     

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This paper discusses the deployment of Genetic algorithm optimization method for synthesis of antenna array radiation pattern in adaptive beamforming. The synthesis problem discussed is to find the weights of the antenna array elements that are optimum to provide the radiation pattern with maximum reduction in the sidelobe level A continuous GA with a population size 10 and a mutation rate of 0.35 with Roulette selection is run for a total of 500 generations using MATLAB and the best result was found for each iteration. This technique proved its effectiveness in improving the performance of the antenna array.

Keywords

Adaptive Beamforming, Sidelobe level, Genetic Algorithm, Linear Antenna Array, Pattern Synthesis, Convergence, Array Factor.
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  • Synthesis of Linear Antenna Array Using Genetic Algorithm with Cost Based Roulette Wheel Selection to Maximize Sidelobe Level Reduction

Abstract Views: 191  |  PDF Views: 4

Authors

T. S. Jeyali Laseetha
Department of Electronics and Communication Engineering, HolyCross Engineering College, Anna University of Technology, Tirunelveli, Tamil Nadu, India
R. Sukanesh
Department of Electronics and Communication Engineering, Thiagarajar College of Engineering, Madurai, Tamil Nadu, India

Abstract


This paper discusses the deployment of Genetic algorithm optimization method for synthesis of antenna array radiation pattern in adaptive beamforming. The synthesis problem discussed is to find the weights of the antenna array elements that are optimum to provide the radiation pattern with maximum reduction in the sidelobe level A continuous GA with a population size 10 and a mutation rate of 0.35 with Roulette selection is run for a total of 500 generations using MATLAB and the best result was found for each iteration. This technique proved its effectiveness in improving the performance of the antenna array.

Keywords


Adaptive Beamforming, Sidelobe level, Genetic Algorithm, Linear Antenna Array, Pattern Synthesis, Convergence, Array Factor.