Wednesday 22nd of November 2017
 

Patterns Antennas Arrays Synthesis Based on Adaptive Particle Swarm Optimization and Genetic Algorithms


Boufeldja Kadri, Miloud Bousahla, Mohamed Brahimi, Ismail Khalil Bousserhane and Bendimerad Fethi Tarek

In recent years, evolutionary optimization (EO) techniques have attracted considerable attention in the design of electromagnetic systems of increasing complexity. This paper presents a comparison between two optimization algorithms for the synthesis of uniform linear and planar antennas arrays, the first one is an adaptive particle swarm optimization (APSO) where the inertia weight and acceleration coefficient are adjusted dynamically according to feedback taken from particles best memories to overcome the limitations of the standard PSO which are: premature convergence, low searching accuracy and iterative inefficiency. The second method is the genetic algorithms (GA) inspired from the processes of the evolution of the species and the natural genetics. The results show that the design of uniform linear and planar antennas arrays using APSO method provides a low side lobe level and achieve faster convergence speed to the optimum solution than those obtained by a GA.

Keywords: antennas arrays, planar arrays, synthesis, optimization methods; adaptive particle swarm algorithm, genetic algorithm

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ABOUT THE AUTHORS

Boufeldja Kadri
Bechar University, Faculty of Sciences and Technologies, Departement of Electronic, Bechar, Algeria

Miloud Bousahla
Abou-Bakr Belkaid University, Engineering Sciences Faculty, Telecommunications Laboratory Tlemcen, Algeria

Mohamed Brahimi
Bechar University, Faculty of Sciences and Technologies, Departement of Electronic, Bechar, Algeria

Ismail Khalil Bousserhane
Bechar University, Faculty of Sciences and Technologies, Departement of Electronic, Bechar, Algeria

Bendimerad Fethi Tarek
Abou-Bakr Belkaid University, Engineering Sciences Faculty, Telecommunications Laboratory Tlemcen, Algeria


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