{"title":"Optimal Design of Antenna Array using Tuned Random Drift Particle Swarm Optimization Algorithm","authors":"Debolina Brahma, Arindam Deb","doi":"10.1109/IEMTRONICS51293.2020.9216378","DOIUrl":null,"url":null,"abstract":"Conventional particle swarm optimization and random drift particle swarm optimization algorithms are applied to the optimal design of a collinear dipole antenna array. The random drift particle swam optimization algorithm is tuned for its best performance by properly choosing the control parameter and it showed a faster convergence rate compared to the conventional particle swarm optimization algorithm. The optimal array designed using the conventional particle swarm optimization algorithm has a beam width of 9 degrees between 1st nulls and maximum side lobe level of -24.17 dB whereas the array designed using the random drift particle swarm optimization algorithm has a beam width of 10 degrees between 1st nulls and maximum side lobe level of -27.46 dB.","PeriodicalId":269697,"journal":{"name":"2020 IEEE International IOT, Electronics and Mechatronics Conference (IEMTRONICS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE International IOT, Electronics and Mechatronics Conference (IEMTRONICS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IEMTRONICS51293.2020.9216378","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Conventional particle swarm optimization and random drift particle swarm optimization algorithms are applied to the optimal design of a collinear dipole antenna array. The random drift particle swam optimization algorithm is tuned for its best performance by properly choosing the control parameter and it showed a faster convergence rate compared to the conventional particle swarm optimization algorithm. The optimal array designed using the conventional particle swarm optimization algorithm has a beam width of 9 degrees between 1st nulls and maximum side lobe level of -24.17 dB whereas the array designed using the random drift particle swarm optimization algorithm has a beam width of 10 degrees between 1st nulls and maximum side lobe level of -27.46 dB.