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}
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.