扩展InSAR2InSAR到Sentinel-1数据

Carla Geara;Colette Gelas;Louis de Vitry;Elise Colin;Florence Tupin
{"title":"扩展InSAR2InSAR到Sentinel-1数据","authors":"Carla Geara;Colette Gelas;Louis de Vitry;Elise Colin;Florence Tupin","doi":"10.1109/LGRS.2025.3558363","DOIUrl":null,"url":null,"abstract":"Interferometric synthetic aperture radar (SAR) parameters’ estimation is a very important and challenging problem. The InSAR2InSAR method previously proposed is one of the few self-supervised methods which aims to estimate InSAR parameters. This method has proven to outperform state-of-the-art methods on simulated synthetic data. However, it has to be extended on real data. In this letter, we demonstrate that Sentinel-1 images acquired in the interferometric wide (IW) swath mode possess the necessary properties to train and apply InSAR2InSAR effectively. In this letter, we demonstrate the ability of InSAR2InSAR to process across-track Sentinel-1 interferometric images with state-of-the-art performances.","PeriodicalId":91017,"journal":{"name":"IEEE geoscience and remote sensing letters : a publication of the IEEE Geoscience and Remote Sensing Society","volume":"22 ","pages":"1-5"},"PeriodicalIF":0.0000,"publicationDate":"2025-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Extending InSAR2InSAR to Sentinel-1 Data\",\"authors\":\"Carla Geara;Colette Gelas;Louis de Vitry;Elise Colin;Florence Tupin\",\"doi\":\"10.1109/LGRS.2025.3558363\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Interferometric synthetic aperture radar (SAR) parameters’ estimation is a very important and challenging problem. The InSAR2InSAR method previously proposed is one of the few self-supervised methods which aims to estimate InSAR parameters. This method has proven to outperform state-of-the-art methods on simulated synthetic data. However, it has to be extended on real data. In this letter, we demonstrate that Sentinel-1 images acquired in the interferometric wide (IW) swath mode possess the necessary properties to train and apply InSAR2InSAR effectively. In this letter, we demonstrate the ability of InSAR2InSAR to process across-track Sentinel-1 interferometric images with state-of-the-art performances.\",\"PeriodicalId\":91017,\"journal\":{\"name\":\"IEEE geoscience and remote sensing letters : a publication of the IEEE Geoscience and Remote Sensing Society\",\"volume\":\"22 \",\"pages\":\"1-5\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2025-04-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE geoscience and remote sensing letters : a publication of the IEEE Geoscience and Remote Sensing Society\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10950418/\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE geoscience and remote sensing letters : a publication of the IEEE Geoscience and Remote Sensing Society","FirstCategoryId":"1085","ListUrlMain":"https://ieeexplore.ieee.org/document/10950418/","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

干涉型合成孔径雷达(SAR)参数估计是一个非常重要且具有挑战性的问题。先前提出的InSAR2InSAR方法是为数不多的旨在估计InSAR参数的自监督方法之一。该方法已被证明在模拟合成数据上优于最先进的方法。然而,它必须在实际数据上进行扩展。在这封信中,我们证明了在干涉宽(IW)条纹模式下获得的Sentinel-1图像具有有效训练和应用InSAR2InSAR所需的属性。在这封信中,我们展示了InSAR2InSAR以最先进的性能处理跨轨道Sentinel-1干涉图像的能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Extending InSAR2InSAR to Sentinel-1 Data
Interferometric synthetic aperture radar (SAR) parameters’ estimation is a very important and challenging problem. The InSAR2InSAR method previously proposed is one of the few self-supervised methods which aims to estimate InSAR parameters. This method has proven to outperform state-of-the-art methods on simulated synthetic data. However, it has to be extended on real data. In this letter, we demonstrate that Sentinel-1 images acquired in the interferometric wide (IW) swath mode possess the necessary properties to train and apply InSAR2InSAR effectively. In this letter, we demonstrate the ability of InSAR2InSAR to process across-track Sentinel-1 interferometric images with state-of-the-art performances.
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
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信