Novel Metaheuristic Optimization Algorithms for Sidelobe Suppression of Linear Antenna Array

Durmuş A.

International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT), Ankara, Turkey, 21 October - 23 December 2021, pp.291-294

  • Publication Type: Conference Paper / Full Text
  • Doi Number: 10.1109/ismsit52890.2021.9604710
  • City: Ankara
  • Country: Turkey
  • Page Numbers: pp.291-294
  • Kayseri University Affiliated: Yes


In this study, the problem of sidelobe suppression in the antenna radiation patterns on which antenna designers work intensively, is discussed. For this optimization problem, analyses are carried out with the newly introduced Honey Badger Algorithm (HBA) and Chameleon Swarm Algorithm (CSA) algorithms in the literature. In addition, to test the performance of these algorithms, Artificial Bee Colony (ABC), and Particle Swarm Optimization (PSO) methods, which are well known in the literature, are also used in sidelobe suppression in antenna arrays. For the statistical comparison of these four optimization methods, thirty independent runs are made, and the results are tabulated.