基于群优化的时调制线性天线阵旁瓣抑制

G. Ram, D. Mandal, R. Kar, S. P. Ghosal
{"title":"基于群优化的时调制线性天线阵旁瓣抑制","authors":"G. Ram, D. Mandal, R. Kar, S. P. Ghosal","doi":"10.1109/CICN.2014.231","DOIUrl":null,"url":null,"abstract":"In this paper evolutionary optimization based improved particle swarm optimization with wavelet mutation (IPSOWM) is used for the improvement of the radiation performance of time modulated linear antenna arrays. In this paper optimal side lobe reduction is achieved with optimized uniform inter-element spacing and optimal switching time sequence of each element. Real coded genetic algorithm (RGA) and conventional particle swarm optimization (PSO) is also used for comparison of results. The approach is illustrated through 32-element. Various results are presented to show the advantage of IPSOWM approach considering maximum side lobe reduction even amplitude excitation weight is uniform.","PeriodicalId":6487,"journal":{"name":"2014 International Conference on Computational Intelligence and Communication Networks","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2014-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Swarm Optimization Based Side Lobe Reduction in Time Modulated Linear Antenna Arrays\",\"authors\":\"G. Ram, D. Mandal, R. Kar, S. P. Ghosal\",\"doi\":\"10.1109/CICN.2014.231\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper evolutionary optimization based improved particle swarm optimization with wavelet mutation (IPSOWM) is used for the improvement of the radiation performance of time modulated linear antenna arrays. In this paper optimal side lobe reduction is achieved with optimized uniform inter-element spacing and optimal switching time sequence of each element. Real coded genetic algorithm (RGA) and conventional particle swarm optimization (PSO) is also used for comparison of results. The approach is illustrated through 32-element. Various results are presented to show the advantage of IPSOWM approach considering maximum side lobe reduction even amplitude excitation weight is uniform.\",\"PeriodicalId\":6487,\"journal\":{\"name\":\"2014 International Conference on Computational Intelligence and Communication Networks\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-11-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 International Conference on Computational Intelligence and Communication Networks\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CICN.2014.231\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 International Conference on Computational Intelligence and Communication Networks","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CICN.2014.231","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

本文将基于进化优化的小波突变改进粒子群优化算法(IPSOWM)用于改进时调线性天线阵列的辐射性能。本文利用最优的均匀元间距和最优的各元切换时间序列来实现最优的旁瓣抑制。采用实编码遗传算法(RGA)和传统粒子群算法(PSO)对结果进行比较。该方法通过32个元素来说明。各种结果表明,考虑最大旁瓣减小,即使振幅激励权是均匀的,ipsom方法具有优势。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Swarm Optimization Based Side Lobe Reduction in Time Modulated Linear Antenna Arrays
In this paper evolutionary optimization based improved particle swarm optimization with wavelet mutation (IPSOWM) is used for the improvement of the radiation performance of time modulated linear antenna arrays. In this paper optimal side lobe reduction is achieved with optimized uniform inter-element spacing and optimal switching time sequence of each element. Real coded genetic algorithm (RGA) and conventional particle swarm optimization (PSO) is also used for comparison of results. The approach is illustrated through 32-element. Various results are presented to show the advantage of IPSOWM approach considering maximum side lobe reduction even amplitude excitation weight is uniform.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Research on Flow Control of all Vanadium Flow Battery Energy Storage Based on Fuzzy Algorithm Synthetic Aperture Radar System Using Digital Chirp Signal Generator Based on the Piecewise Higher Order Polynomial Interpolation Technique Frequency-Domain Equalization for E-Band Transmission System A Mean-Semi-variance Portfolio Optimization Model with Full Transaction Costs Detailed Evaluation of DEM Interpolation Methods in GIS Using DGPS Data
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1