THE FINE-GRAINED PARALLEL MICRO-GENETIC ALGORITHM AND ITS APPLICATION TO BROADBAND CONICAL CORRUGATED-HORN ANTENNA | Zendy

Lei Chang | Zendy; Haijing Zhou | Zendy; Ling-Lu Chen | Zendy; Xiang-Zheng Xiong | Zendy; Cheng Liao | Zendy

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THE FINE-GRAINED PARALLEL MICRO-GENETIC ALGORITHM AND ITS APPLICATION TO BROADBAND CONICAL CORRUGATED-HORN ANTENNA

Author(s) -

Lei Chang,

Haijing Zhou,

Ling-Lu Chen,

Xiang-Zheng Xiong,

Cheng Liao

Publication year - 2013

Publication title -

electromagnetic waves

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.437

H-Index - 89

eISSN - 1559-8985

pISSN - 1070-4698

DOI - 10.2528/pier13030908

Subject(s) - french horn , broadband , horn antenna , conical surface , computer science , genetic algorithm , antenna (radio) , feed horn , acoustics , telecommunications , directional antenna , engineering , radiation pattern , physics , slot antenna , periscope antenna , mechanical engineering , machine learning

The flne-grained parallel micro-genetic algorithm (FGP- MGA) is developed to solve antenna design problems. The synthesis of uniformly exited unequally spaced array is presented. Comparison with the micro-genetic algorithm (MGA) has been carried out. It is seen that the FGPMGA signiflcantly outperforms MGA, in terms of both the convergence rate and exploration ability. The FGPMGA can also reduce the optimization time. Then the FGPMGA and the body of revolution flnite-difierence time-domain (BOR-FDTD) are combined to achieve an automated design process for conical corrugated-horn antenna. Numerical simulation results show that the horn antenna has good impedance matching (the VSWR is less than 1.5), stable beamwidth and gain, as well as good rotation symmetry patterns over the whole band 8»13GHz.

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