从序列SAR子孔径图像获取海洋动态特征的改进相位相关方法

Q2 Physics and Astronomy 雷达学报 Pub Date : 2013-01-01 DOI:10.3724/sp.j.1300.2013.13016
Wang Xiaoqing, Su Hai-qing, Chong Jin-song
{"title":"从序列SAR子孔径图像获取海洋动态特征的改进相位相关方法","authors":"Wang Xiaoqing, Su Hai-qing, Chong Jin-song","doi":"10.3724/sp.j.1300.2013.13016","DOIUrl":null,"url":null,"abstract":"Dynamic features are important aspects of the ocean. However the dynamic information is lost in most conventional Synthetic Aperture Radar (SAR) image processing methods, because they treat the image as an instantaneous state of the observed area. In fact, we can obtain dynamic features of the ocean from sequential sub-aperture images, because we know that the different parts of the azimuthal aperture correspond to different imaging instances. A key step for retrieving the dynamic features from sequential images is image-matching. However, the heavy noise characteristic of sub-aperture SAR images renders the traditional image-matching methods ineffective. In this paper we propose an image matching method based on improved phase correlation to deal with the heavy noise problem of SAR sub-aperture images. Experimental results show that the improved image-matching method presents an accuracy of 0.15 pixel and noise robustness. The analysis indicates that the improved algorithm is competent for obtaining dynamic information from the medium resolution airborne SAR images or high resolution spaceborne SAR images with 0.15-0.3 m/s estimation precision under most SNR conditions. The improved algorithm was used on an airborne SAR data to retrieve the movement velocity. The retrieved velocity ranged from 0.05-0.5 m/s, which seems to be reasonable value for the ocean current velocity.","PeriodicalId":37701,"journal":{"name":"雷达学报","volume":"1 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2013-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"An Improved Phase Correlation Method for Obtaining Dynamic Feature of the Ocean from Sequential SAR Sub-aperture Images\",\"authors\":\"Wang Xiaoqing, Su Hai-qing, Chong Jin-song\",\"doi\":\"10.3724/sp.j.1300.2013.13016\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Dynamic features are important aspects of the ocean. However the dynamic information is lost in most conventional Synthetic Aperture Radar (SAR) image processing methods, because they treat the image as an instantaneous state of the observed area. In fact, we can obtain dynamic features of the ocean from sequential sub-aperture images, because we know that the different parts of the azimuthal aperture correspond to different imaging instances. A key step for retrieving the dynamic features from sequential images is image-matching. However, the heavy noise characteristic of sub-aperture SAR images renders the traditional image-matching methods ineffective. In this paper we propose an image matching method based on improved phase correlation to deal with the heavy noise problem of SAR sub-aperture images. Experimental results show that the improved image-matching method presents an accuracy of 0.15 pixel and noise robustness. The analysis indicates that the improved algorithm is competent for obtaining dynamic information from the medium resolution airborne SAR images or high resolution spaceborne SAR images with 0.15-0.3 m/s estimation precision under most SNR conditions. The improved algorithm was used on an airborne SAR data to retrieve the movement velocity. The retrieved velocity ranged from 0.05-0.5 m/s, which seems to be reasonable value for the ocean current velocity.\",\"PeriodicalId\":37701,\"journal\":{\"name\":\"雷达学报\",\"volume\":\"1 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"雷达学报\",\"FirstCategoryId\":\"1093\",\"ListUrlMain\":\"https://doi.org/10.3724/sp.j.1300.2013.13016\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"Physics and Astronomy\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"雷达学报","FirstCategoryId":"1093","ListUrlMain":"https://doi.org/10.3724/sp.j.1300.2013.13016","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Physics and Astronomy","Score":null,"Total":0}
引用次数: 1

摘要

动态特征是海洋的重要方面。然而,传统的合成孔径雷达(SAR)图像处理方法大多将图像视为观测区域的瞬时状态,因而丢失了动态信息。实际上,我们可以从序列子孔径图像中获得海洋的动态特征,因为我们知道方位孔径的不同部分对应不同的成像实例。从序列图像中提取动态特征的关键步骤是图像匹配。然而,子孔径SAR图像的高噪声特性使得传统的图像匹配方法失效。针对SAR子孔径图像的重噪声问题,提出了一种基于改进相位相关的图像匹配方法。实验结果表明,改进后的图像匹配方法具有0.15像素的精度和噪声鲁棒性。分析表明,在大多数信噪比条件下,改进算法能够以0.15 ~ 0.3 m/s的估计精度从中分辨率机载SAR图像或高分辨率星载SAR图像中获取动态信息。将改进后的算法应用于机载SAR数据的运动速度检索。反演速度范围为0.05 ~ 0.5 m/s,这是比较合理的海流速度值。
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
An Improved Phase Correlation Method for Obtaining Dynamic Feature of the Ocean from Sequential SAR Sub-aperture Images
Dynamic features are important aspects of the ocean. However the dynamic information is lost in most conventional Synthetic Aperture Radar (SAR) image processing methods, because they treat the image as an instantaneous state of the observed area. In fact, we can obtain dynamic features of the ocean from sequential sub-aperture images, because we know that the different parts of the azimuthal aperture correspond to different imaging instances. A key step for retrieving the dynamic features from sequential images is image-matching. However, the heavy noise characteristic of sub-aperture SAR images renders the traditional image-matching methods ineffective. In this paper we propose an image matching method based on improved phase correlation to deal with the heavy noise problem of SAR sub-aperture images. Experimental results show that the improved image-matching method presents an accuracy of 0.15 pixel and noise robustness. The analysis indicates that the improved algorithm is competent for obtaining dynamic information from the medium resolution airborne SAR images or high resolution spaceborne SAR images with 0.15-0.3 m/s estimation precision under most SNR conditions. The improved algorithm was used on an airborne SAR data to retrieve the movement velocity. The retrieved velocity ranged from 0.05-0.5 m/s, which seems to be reasonable value for the ocean current velocity.
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
雷达学报
雷达学报 Physics and Astronomy-Instrumentation
CiteScore
4.10
自引率
0.00%
发文量
882
期刊介绍: Information not localized
期刊最新文献
Integrated Chip Technologies for Microwave Photonics Distributed Multi-target Localization System Based on Optical Wavelength Division Multiplexing Network A Novel Cluster-Analysis Algorithm Based on MAP Framework for Multi-baseline InSAR Height Reconstruction A Dynamic and Adaptive Selection Radar Tracking Method Based on Information Entropy An Aircraft Detection Method Based on Convolutional Neural Networks in High-Resolution SAR Images
×
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