Zhiyuan Xue;Liang Li;Yijiang Nan;Fei Zou;Zongxiang Xu;Tianyuan Yang;Robert Wang
{"title":"A Sinogram Decimation Fast Back-Projection Algorithm for Strip-Map SAR Imaging","authors":"Zhiyuan Xue;Liang Li;Yijiang Nan;Fei Zou;Zongxiang Xu;Tianyuan Yang;Robert Wang","doi":"10.1109/JSTARS.2025.3544259","DOIUrl":null,"url":null,"abstract":"In this article, a novel sinogram decimation fast back-projection (SD-FBP) algorithm for strip-map synthetic aperture radar (SAR) imaging is proposed. We first review the back-projection (BP) and the fast factorized BP (FFBP) algorithms, then analyze the cause of the FFBP imaging degradation theoretically based on the combination of SAR imaging and the sinogram concept of computed tomography, illustrating that the degradation is much more severe for strip-map mode. Based on the SAR sinogram, the SD-FBP algorithm is proposed to mitigate the FFBP degradation for strip-map SAR imaging. The complexity of the SD-FBP is analyzed and compared with that of the FFBP and the Cartesian factorized BP (CFBP). The superiority of the SD-FBP algorithm is validated using the simulation and real spaceborne strip-map SAR data, e.g., Sentinel-1, Gaofen-3, and LuTan-1. The results show that the SD-FBP can tackle the FFBP imaging degradation for strip-map SAR, and runs faster than the FFBP and the CFBP.","PeriodicalId":13116,"journal":{"name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","volume":"18 ","pages":"6790-6805"},"PeriodicalIF":4.7000,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10897897","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","FirstCategoryId":"5","ListUrlMain":"https://ieeexplore.ieee.org/document/10897897/","RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0
Abstract
In this article, a novel sinogram decimation fast back-projection (SD-FBP) algorithm for strip-map synthetic aperture radar (SAR) imaging is proposed. We first review the back-projection (BP) and the fast factorized BP (FFBP) algorithms, then analyze the cause of the FFBP imaging degradation theoretically based on the combination of SAR imaging and the sinogram concept of computed tomography, illustrating that the degradation is much more severe for strip-map mode. Based on the SAR sinogram, the SD-FBP algorithm is proposed to mitigate the FFBP degradation for strip-map SAR imaging. The complexity of the SD-FBP is analyzed and compared with that of the FFBP and the Cartesian factorized BP (CFBP). The superiority of the SD-FBP algorithm is validated using the simulation and real spaceborne strip-map SAR data, e.g., Sentinel-1, Gaofen-3, and LuTan-1. The results show that the SD-FBP can tackle the FFBP imaging degradation for strip-map SAR, and runs faster than the FFBP and the CFBP.
期刊介绍:
The IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing addresses the growing field of applications in Earth observations and remote sensing, and also provides a venue for the rapidly expanding special issues that are being sponsored by the IEEE Geosciences and Remote Sensing Society. The journal draws upon the experience of the highly successful “IEEE Transactions on Geoscience and Remote Sensing” and provide a complementary medium for the wide range of topics in applied earth observations. The ‘Applications’ areas encompasses the societal benefit areas of the Global Earth Observations Systems of Systems (GEOSS) program. Through deliberations over two years, ministers from 50 countries agreed to identify nine areas where Earth observation could positively impact the quality of life and health of their respective countries. Some of these are areas not traditionally addressed in the IEEE context. These include biodiversity, health and climate. Yet it is the skill sets of IEEE members, in areas such as observations, communications, computers, signal processing, standards and ocean engineering, that form the technical underpinnings of GEOSS. Thus, the Journal attracts a broad range of interests that serves both present members in new ways and expands the IEEE visibility into new areas.