基于矩量法的机器学习二维散射分析

2020 IEEE International Symposium on Antennas and Propagation and North American Radio Science Meeting Pub Date : 2020-07-05 DOI:10.1109/IEEECONF35879.2020.9330266

D. Olćan, J. Petrovic, B. Kolundžija

{"title":"基于矩量法的机器学习二维散射分析","authors":"D. Olćan, J. Petrovic, B. Kolundžija","doi":"10.1109/IEEECONF35879.2020.9330266","DOIUrl":null,"url":null,"abstract":"Machine learning is used to determine the polynomial regression of the coefficients of surface currents approximation for a curvilinear 2-D scatterer. The training data are obtained using method of moments with higher order basis functions and Galerkin testing procedure. The effect of polynomial regression order to the accuracy of calcualted radar cross-section is explored.","PeriodicalId":135770,"journal":{"name":"2020 IEEE International Symposium on Antennas and Propagation and North American Radio Science Meeting","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2020-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Machine Learning for 2-D Scattering Analysis using Method of Moments\",\"authors\":\"D. Olćan, J. Petrovic, B. Kolundžija\",\"doi\":\"10.1109/IEEECONF35879.2020.9330266\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Machine learning is used to determine the polynomial regression of the coefficients of surface currents approximation for a curvilinear 2-D scatterer. The training data are obtained using method of moments with higher order basis functions and Galerkin testing procedure. The effect of polynomial regression order to the accuracy of calcualted radar cross-section is explored.\",\"PeriodicalId\":135770,\"journal\":{\"name\":\"2020 IEEE International Symposium on Antennas and Propagation and North American Radio Science Meeting\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-07-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 IEEE International Symposium on Antennas and Propagation and North American Radio Science Meeting\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IEEECONF35879.2020.9330266\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE International Symposium on Antennas and Propagation and North American Radio Science Meeting","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IEEECONF35879.2020.9330266","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 2

摘要

利用机器学习确定了曲线二维散射体表面电流近似系数的多项式回归。利用高阶基函数矩量法和伽辽金检验程序获得训练数据。探讨了多项式回归阶对雷达截面计算精度的影响。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Machine Learning for 2-D Scattering Analysis using Method of Moments

Machine learning is used to determine the polynomial regression of the coefficients of surface currents approximation for a curvilinear 2-D scatterer. The training data are obtained using method of moments with higher order basis functions and Galerkin testing procedure. The effect of polynomial regression order to the accuracy of calcualted radar cross-section is explored.

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

2020 IEEE International Symposium on Antennas and Propagation and North American Radio Science Meeting

自引率

0.00%

发文量