利用GEK代理模型的天线快速多目标优化设计

doi:10.3969/j.issn.1001-2400.2018.02.022

Abstract

Abstract:

Based on classical optimization algorithms and electromagnetic simulations, traditional antenna optimization method is inefficient, especially when it is used to solve the complex antenna multi-objective optimization problem. With the introduction of the genetic operator, the paper proposes an efficient global optimization algorithm named the Multi-Gradient Descent Algorithm Hybrid with the Genetic Operator to alleviate the problem above. For the merits of quick establishment and reduced samples scale, the Gradient-Enhanced Kriging(GEK) model is invoked by the proposed algorithm as the surrogate of antenna electromagnetic analysis. A Novel broadband UHF monopole antenna enabled by anisotropic Ⅰ-shaped periodic structure cladding and a dual-band UHF antenna together with its anti-jamming array antenna reserved for the private airborne communication system are designed with the proposed optimization method. The necessary electromagnetic simulation time of the proposed method is 10.30％ and that of the traditional optimization method is 18.96％, which verifies the merit of high efficiency.

Key words: antenna multi-objective optimization, mulit-gradient descent algorithm, genetic operator, surrogate model, gradient-enhanced Kriging model

WANG Danqing;LI Ping. Expedited antenna multi-objective optimization method based on gradient-enhanced kriging surrogate model[J].Journal of Xidian University, 2018, 45(2): 129-134+165.

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Expedited antenna multi-objective optimization method based on gradient-enhanced kriging surrogate model

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