Journal of Xidian University

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

WANG Danqing;LI Ping   

  1. (Department of Information Engineering, Engineering Univ. of PAP, Xi'an 710086, China)
  • Received:2017-05-23 Online:2018-04-20 Published:2018-06-06


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