Journal of Xidian University ›› 2023, Vol. 50 ›› Issue (3): 202-212.doi: 10.19665/j.issn1001-2400.2023.03.019

• Information and Communications Engineering & Electronic Science and Technology • Previous Articles    

Improved arithmetic optimization algorithm for sparse planar arrays synthesis

GUO Qiang1,2(),LIU Congye1,2(),WANG Yani1,2(),WANG Yong1,2(),CHERNOGOR Leonid3()   

  1. 1. College of Information and Communication Engineering,Harbin Engineering University,Harbin 150001,China
    2. Key Laboratory of Advanced Marine Communication and Information Technology,Ministry of Industry and Technology,Harbin 150001,China
    3. Department of Space Radiophysics,V.N.Karazin Kharkiv National Univrsity,Kharkov 61022,Ukraine
  • Received:2022-07-19 Online:2023-06-20 Published:2023-10-13
  • Contact: Yani WANG E-mail:guoqiang@hrbeu.edu.cn;lcy@hrbeu.edu.cn;178655165@hrbeu.edu.cn;wangyong@hrbeu.edu.cn;leonid.f.chernogor@gmail.com

Abstract:

An array antenna synthesis algorithm based on an improved arithmetic optimization algorithm is proposed to address the problems of sidelobe level suppression and null steering synthesis of sparse planar array radiation pattern.First,the math optimizer accelerated in the arithmetic optimization algorithm is reconstructed using a nonlinear function to balance the exploitation and exploration process weights.Second,top three best individuals are used instead of the current best optimal individuals for exploration and exploitation and an elite variation strategy is introduced to enhance the ability of the algorithm to escape from the local optimum and improve the convergence accuracy of the algorithm.Finally,an adaptive matrix mapping law is proposed to judge the current array element distribution,and if it does not satisfy the minimum array element spacing constraint,it is adjusted by an adjustment strategy to avoid infeasible solutions while ensuring the degrees of freedom of the array element.Compared with the existing algorithms in the literature,the improved arithmetic optimization algorithm has improved the optimization accuracy and stability of both single-peak and multi-peak standard test functions; In the experiments of sparse planar array sidelobe level suppression and null synthesis,the proposed algorithm can synthesize a better peak sidelobe level and null depth,which proves the effectiveness of the proposed algorithm.

Key words: array synthesis, sparse arrays, matrix mapping laws, arithmetic optimization algorithms

CLC Number: 

  • TN92