{"title":"Uncrewed Aerial Vehicle (UAV)-Based, K-Band Interferometric Synthetic Aperture Radar (SAR)","authors":"Yaxuan Li;Ali Bekar;Marco Martorella;Michail Antoniou","doi":"10.1109/TRS.2026.3661483","DOIUrl":null,"url":null,"abstract":"This article proposes the study and development of interferometric synthetic aperture radar (InSAR) from compact, high-frequency radar sensors onboard commercial uncrewed aerial vehicles (UAVs), (often referred to as “drones”) to create precision digital elevation models (DEMs). The potential of such InSAR systems, due to the higher operating frequency and target proximity, is quantified, but it is also shown how the same features, combined with the instability of UAV platforms, lead to motion errors that either deteriorate or altogether deny capability. This article thus quantifies acceptable motion error limits and shows how complex autofocus can restore height estimation performance, through analytical modeling that is verified by simulation and validated through outdoor experiments with a 24 GHz UAV-based demonstrator. To our knowledge, this is the first demonstration of a UAV-based InSAR system in this high-frequency band.","PeriodicalId":100645,"journal":{"name":"IEEE Transactions on Radar Systems","volume":"4 ","pages":"535-548"},"PeriodicalIF":0.0000,"publicationDate":"2026-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11414200","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Radar Systems","FirstCategoryId":"1085","ListUrlMain":"https://ieeexplore.ieee.org/document/11414200/","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This article proposes the study and development of interferometric synthetic aperture radar (InSAR) from compact, high-frequency radar sensors onboard commercial uncrewed aerial vehicles (UAVs), (often referred to as “drones”) to create precision digital elevation models (DEMs). The potential of such InSAR systems, due to the higher operating frequency and target proximity, is quantified, but it is also shown how the same features, combined with the instability of UAV platforms, lead to motion errors that either deteriorate or altogether deny capability. This article thus quantifies acceptable motion error limits and shows how complex autofocus can restore height estimation performance, through analytical modeling that is verified by simulation and validated through outdoor experiments with a 24 GHz UAV-based demonstrator. To our knowledge, this is the first demonstration of a UAV-based InSAR system in this high-frequency band.