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The developments of the radar sea target recognition technologies are predicted based on the available researches., authors=HE Zhihua, DUAN Jia, LU Da, authorsList=HE Zhihua, DUAN Jia, LU Da, authorCompany=AVIC Leihua Electronic Technology Research Institute, Wuxi 214063, China, correspAuthors=null, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=ksXlIIDI4frSrA0C99zzow==, pdfFileSize=1793422, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1242136449810772911, articleId=1242136447365493669, tenantId=1146029695717560320, journalId=1146031591421210625, language=CN, title=雷达海面目标识别技术研究进展, columnId=1242116902361830275, journalTitle=科技导报, columnName=专题论文, runingTitle=null, highlight=null, articleAbstract=针对雷达海面目标识别特征数据缺乏和识别算法推广能力差等问题,从雷达目标电磁散射特性和目标分类识别两方面总结了雷达海面目标识别技术的研究热点和发展趋势。围绕海面目标雷达特性,从电磁散射测量和建模两个方面综述了国内外研究现状;从低分辨雷达回波、高分辨距离像、高分辨雷达图像3方面综述了海面目标识别技术发展现状;介绍了雷达海面目标识别工程应用情况;最后展望了海面目标识别技术的发展趋势。, authors=贺治华, 段佳, 芦达, authorsList=贺治华, 段佳, 芦达, authorCompany=中国航空工业集团公司雷华电子技术研究所, 无锡 214063, correspAuthors=null, authorNote=贺治华,高级工程师,研究方向为雷达目标识别、微动特征分析等,电子信箱:shimenguest@163.com, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=NU5v7qH/NE4BYBwFxRfGRA==, pdfFileSize=1793422, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null)}, authors=[Author(id=1277575998182962125, tenantId=1146029695717560320, journalId=null, articleId=1242136447365493669, orderNo=null, firstName=null, 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A review of radar sea target recognition technology
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出版时间: 2017-10-28 doi: 10.3981/j.issn.1000-7857.2017.20.006
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针对雷达海面目标识别特征数据缺乏和识别算法推广能力差等问题,从雷达目标电磁散射特性和目标分类识别两方面总结了雷达海面目标识别技术的研究热点和发展趋势。围绕海面目标雷达特性,从电磁散射测量和建模两个方面综述了国内外研究现状;从低分辨雷达回波、高分辨距离像、高分辨雷达图像3方面综述了海面目标识别技术发展现状;介绍了雷达海面目标识别工程应用情况;最后展望了海面目标识别技术的发展趋势。
雷达海面目标识别  /  电磁散射建模  /  目标分类与识别
The lack of feature data and the poor extending capability of the radar target recognition algorithms are two main problems for the radar sea target recognition, which have attracted many researches. This paper reviews the studies of the radar sea target recognition in two aspects, namely, the electro-magnetic modeling and the radar target classification algorithms. For the analysis of sea target electromagnetic behaviors, the review is focused on both the measurement and the modeling of the electro-magnetic scattering. For the radar sea target recognition technologies, the review covers the methods based on the narrow band, the high resolution range, and the high resolution images. The developments of the radar sea target recognition technologies are predicted based on the available researches.
radar sea target recognition  /  electro-magnetic modeling  /  target classification and recognition
贺治华, 段佳, 芦达. 雷达海面目标识别技术研究进展. 科技导报, 2017 , 35 (20) : 61 -68 . DOI: 10.3981/j.issn.1000-7857.2017.20.006
HE Zhihua, DUAN Jia, LU Da. A review of radar sea target recognition technology[J]. Science & Technology Review, 2017 , 35 (20) : 61 -68 . DOI: 10.3981/j.issn.1000-7857.2017.20.006
2017年第35卷第20期
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doi: 10.3981/j.issn.1000-7857.2017.20.006
  • 接收时间:2017-09-25
  • 首发时间:2017-10-31
  • 出版时间:2017-10-28
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  • 收稿日期:2017-09-25
  • 修回日期:2017-10-10
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2种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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