确定贝塞尔光束源参数的蒙特卡罗方法

I. Platt, A. Tan, I. Woodhead, K. Eccleston
{"title":"确定贝塞尔光束源参数的蒙特卡罗方法","authors":"I. Platt, A. Tan, I. Woodhead, K. Eccleston","doi":"10.1109/ICSENST.2016.7796332","DOIUrl":null,"url":null,"abstract":"In this paper we derive a robust Markov Chain Monte Carlo formulation to determine the suitable driver amplitudes for a microwave antenna to generate a Bessel beam. We show that the resulting solutions provide a robust driver for a well collimated beam with high SNR over a region of 0.5-3 m, easily sufficient for close proximity sampling.","PeriodicalId":297617,"journal":{"name":"2016 10th International Conference on Sensing Technology (ICST)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"A Monte Carlo approach to determining bessel beam source parameters\",\"authors\":\"I. Platt, A. Tan, I. Woodhead, K. Eccleston\",\"doi\":\"10.1109/ICSENST.2016.7796332\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper we derive a robust Markov Chain Monte Carlo formulation to determine the suitable driver amplitudes for a microwave antenna to generate a Bessel beam. We show that the resulting solutions provide a robust driver for a well collimated beam with high SNR over a region of 0.5-3 m, easily sufficient for close proximity sampling.\",\"PeriodicalId\":297617,\"journal\":{\"name\":\"2016 10th International Conference on Sensing Technology (ICST)\",\"volume\":\"27 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 10th International Conference on Sensing Technology (ICST)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSENST.2016.7796332\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 10th International Conference on Sensing Technology (ICST)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSENST.2016.7796332","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

本文导出了一个鲁棒的马尔可夫链蒙特卡罗公式,用于确定微波天线产生贝塞尔波束的合适驱动幅值。我们表明,所得的解决方案为在0.5-3 m区域内具有高信噪比的准直光束提供了强大的驱动器,很容易实现近距离采样。
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
A Monte Carlo approach to determining bessel beam source parameters
In this paper we derive a robust Markov Chain Monte Carlo formulation to determine the suitable driver amplitudes for a microwave antenna to generate a Bessel beam. We show that the resulting solutions provide a robust driver for a well collimated beam with high SNR over a region of 0.5-3 m, easily sufficient for close proximity sampling.
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
Advanced AODV approach for efficient detection and mitigation of wormhole attack in MANET Taste sensor using strongly hydrophobic membranes to measure hydrophobic substances Optimal design work for high-frequency quartz resonators A novel hybrid based recommendation system based on clustering and association mining Highly sensitive visible and near-infrared photo-FET based on PbS quantum dots embedded in the gate insulator
×
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