全部 标题 作者
关键词 摘要

OALib Journal期刊
ISSN: 2333-9721
费用:99美元

查看量下载量

相关文章

更多...

基于结构特征的SAR船只类型识别能力分析

, PP. 146-152

Full-Text   Cite this paper   Add to My Lib

Abstract:

References

[1]  MARGARIT G, MALLORQUI J J, RIUS J M, et al. On the usage of GRECOSAR, an orbital polarimetric SAR simulator of complex targets for vessel classification studies [J]. IEEE Trans Geosci Remote Sensing, 2006, 4412: 3517—3526.
[2]  BACHMANN C M, MUSMAN S A, SCHULTZ A. Lateral inhibition neural networks for classification of simulated radar imagery // IEEE International Conference on Neural Networks. Baltimore:Lucas S M,1992:115—120.
[3]  ASKARI F, ZERR B. Automatic approach to ship detection in spaceborne synthetic aperture radar imagery: an assessment of ship detection capability using RADARSAT . Technical Report SACLANTCEN-SR-338. La Spezia, Italy: SACLANT Undersea Research Centre,2000.36.
[4]  种劲松. 合成孔径雷达图像舰船目标检测算法与应用研究 . 北京: 中国科学院电子学研究所,2002.
[5]  ZHANG Xi, ZHANG Jie, JI Yong-gang. Comparison and evaluation of ship target detection algorithms with SAR images. European Space Agency, (Special Publication) ESA SP, n 656 SP //Proceedings of SeaSAR 2008. Rome:ESA.2008: 4.
[6]  高贵,计科峰,匡纲要,等.高分辨率SAR图像目标峰值特征提取[J].信息处理,2005, 21(3):232—235.
[7]  王隽, 杨劲松, 黄韦艮, 等. 基于极化SAR目标分解理论的船只几何结构初步分析 //第二届微波遥感技术研讨会. 北京: 中国空间科学学会, 2006:152—160.
[8]  张晰. 星载SAR舰船目标探测实验研究[M]. 青岛: 中国海洋大学, 2008.
[9]  高贵,计科峰,匡纲要,等.高分辨率SAR图像目标峰值提取及峰值稳定性分析[J].电子与信息学报,2005, 27(4):561—565.
[10]  MARGARIT G, FABREGAS X, MALLORQUI J J. Study of the vessel speed and sea swell effects on simulated polarimetric high resolution SAR images // STEIN T I. Proceedings of IGARSS2004. US IEEE 2004 International Geoscience and Remote Sensing Symposium. 2004: 603—606.
[11]  OSMAN H, BLOSTEIN S, GAGNON L. Classification of ships in airborne sar imagery using back propagation neural networks [J]. SPIE Proc, 1997, 3161:126—136.

Full-Text

Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133