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4th World Congress on Information and Communication Technologies (WICT)

作者： Bera, Rajesh Mandal, Durbadal Kar, Rajib Ghoshal, Sakti Prasad Natl Inst Technol Durgapur Dept Elect & Commun Engn Durgapur W Bengal India Natl Inst Technol Durgapur Dept Elect Engn Durgapur W Bengal India

ISBN: (纸本)9781479981144

In this paper, the optimal thinning of two-ring concentric hexagonal array (CHA) of uniformly excited isotropic antennas which can generate directive beam with minimum relative Side Lobe Level (SLL) is described. The Improved Particle Swarm Optimization (IPSO) method, which represents a new approach for optimization problems in electromagnetic, is used in the optimization process. To determine an optimal set of 'ON-OFF' elements that provide a radiation pattern with maximum SLL reduction, the IPSO algorithm is used. The simulation results show that the number of antenna array elements can be brought down more than 50% of total isotropic elements with simultaneous reduction in Side Lobe Level (SLL) with an approximately fixed first null beam width (FNBW). Particle Swarm Optimization (PSO), as well is also adopted to compare the results of above IPSO.

关键词： thinned array particle swarm optimization Improved particle swarm optimization concentric hexagonal array side lobe level

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Thinned concentric hexagonal Antenna array Synthesis using Craziness based Particle Swarm Optimization

Thinned Concentric Hexagonal Antenna Array Synthesis using C...

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International Conference on Microwave and Photonics (ICMAP)

作者： Bera, Rajesh Mandal, Durbadal Ghoshal, Sakti Prasad Kar, Rajib Natl Inst Technol Durgapur Dept Elect Commun Engn Durgapur W Bengal India Natl Inst Technol Dept Elect Engn Durgapur India

ISBN: (纸本)9781479915736;9781479921751

This paper describes optimal thinning of concentric hexagonal array (CHA) of uniformly excited isotropic antennas which can generate directive beam with minimum relative Side Lobe Level (SLL). The Craziness Based Particle Swarm Optimization (CRPSO) method, which represents a new approach for optimization problems in electromagnetics, is used in the optimization process. The CRPSO is used to determine an optimal set of 'ON-OFF' elements that provide a radiation pattern with maximum SLL reduction. The simulation results show that the number of antenna array elements can be brought down to 60% of total isotropic elements with simultaneous reduction in SLL with an approximately fixed first null beam width (FNBW). Conventional Particle Swarm Optimization (PSO) is also adopted to compare the results of above CRPSO.

关键词： Thinned array Particle swarm optimization Craziness based particle swarm optimization concentric hexagonal array Side lobe lebel

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Optimal Design of Single and Multi-ring Planar array Antenna Using Simplex-PSO

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IETE JOURNAL OF RESEARCH 2017年第6期63卷 881-892页

作者： Bera, Rajesh Mandal, Durbadal Kar, Rajib Ghoshal, Sakti Prasad NIT Durgapur Dept ECE Durgapur India NIT Durgapur Dept EE Durgapur India

In this paper, optimal design of single-ring and multi-ring circular array, hexagonal array, and elliptical array of isotropic antenna has been carried out using Simplex Particle Swarm Optimization (Simplex-PSO). The synthesis of the array geometry is first formulated as an optimization problem with the goal of side lobe level reduction and is then solved using Simplex-PSO algorithm for optimum current excitations. To overcome the premature convergence characteristic of PSO, Simplex-PSO is considered while preserving the fast converging property of PSO. Two design examples are presented which illustrate the effectiveness of Simplex-PSO algorithm, and the optimization goal for each example is easily achieved. The design results obtained using Simplex-PSO are superior to those obtained using popular algorithms like PSO and its variant craziness-based PSO (CRPSO) and PSO with aging leader and challengers (ALC-PSO) in a statistically significant way.

关键词： concentric circular array concentric elliptical array concentric hexagonal array Directivity Evolutionary optimization Side lobe level Simplex-PSO

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