SIDELOBE REDUCTION OF LINEAR ANTENNA ARRAY BY POSITION-ONLY CONTROL USING NOVEL METAHEURISTIC OPTIMIZATION METHODS

Year 2022, , 171 - 179, 18.08.2022

Ali Durmuş , Zafer Yıldırım

https://doi.org/10.31796/ogummf.1012709

Abstract

In this study, the positions only of linear antenna array (LAA) elements are optimized for the first time in the literature by using Honey Badger Algorithm (HBA) and Chameleon Swarm Algorithm (CSA) methods, one of the new metaheuristic algorithms, for antenna design with the desired radiation pattern. LAAs with 10, 12, 24 and 32 elements are considered in the simulations. While designing the antenna, the half-beam power width (HPBW) of the antenna array is kept at a minimum level and the maximum sidelobe level (MSL) is suppressed as much as possible. In addition, to test the performance and accuracy of the HBA and CSA methods, the results obtained with the swarm-based metaheuristic algorithms Artificial Bee Colony (ABC) and Particular Swarm Algorithm (PSO) methods, which are quite well known in the literature are compared. As a result of these comparisons, the antenna design with high directivity, gain and desired pattern has been successfully obtained with the HBA and CSA optimization methods.

Keywords

Artificial intelligence, Optimization, Antenna array synthesis, Maximum sidelobe reduction

YENİ METASEZGİSEL OPTİMİZASYON YÖNTEMLERİNİ KULLANARAK YALNIZCA KONUM KONTROLÜYLE DOĞRUSAL ANTEN DİZİLERİNİN YAN DEMET SEVİYELERİNİN BASTIRILMASI

Abstract

Bu çalışmada, istenen ışıma diyagramına sahip anten tasarımı için yeni metasezgisel algoritmalardan biri olan Bal Porsuğu Algoritması (Honey Badger Algorithm-HBA) ve Bukalemun Sürüsü Algoritması (Chameleon Swarm Algorithm-CSA) yöntemleri kullanılarak lineer anten dizi (Linear Antenna Array-LAA) elemanlarının konumları optimize edilmiştir. Simülasyonlarda 10, 12, 24 ve 32 elemanlı Lineer anten dizileri dikkate alınmıştır. Anten tasarımı yapılırken dizinin yarı demet güç genişliği (Half Power Beam Width-HPBW) minimum seviyede tutulmuş ve maksimum yan demet seviyesi mümkün olduğunca bastırılmıştır. Ayrıca HBA ve CSA yöntemlerinin performans ve doğruluğunu test etmek için literatürde oldukça iyi bilinen sürü tabanlı metasezgisel algoritmalar Yapay Arı Kolonisi (ABC) ve Parçacık Sürüsü Optimizasyonu (PSO) yöntemleri ile elde edilen sonuçlar karşılaştırılarak verilmiştir. Bu karşılaştırmalar sonucunda, HBA ve CSA optimizasyon yöntemleri ile yüksek yönlülük, kazanç ve istenilen ışıma diyagramına sahip anten tasarımı başarılı bir şekilde elde edilmiştir.

Keywords

Yapay zeka, Optimizasyon, Anten dizi sentezi, Maksimum yan demet bastırma

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