A Sinogram Decimation Fast Back-Projection Algorithm for Strip-Map SAR Imaging

IF 5.3 2区地球科学 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing Pub Date : 2025-02-21 DOI:10.1109/JSTARS.2025.3544259

Zhiyuan Xue;Liang Li;Yijiang Nan;Fei Zou;Zongxiang Xu;Tianyuan Yang;Robert Wang

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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.

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一种用于条形SAR成像的正弦图抽取快速反投影算法

提出了一种用于条形合成孔径雷达（SAR）成像的正弦图抽取快速反投影算法。本文首先对反投影（BP）和快速分解BP （FFBP）算法进行了综述，然后结合SAR成像和计算机断层扫描的正弦图概念，从理论上分析了FFBP成像退化的原因，指出条带图模式下的退化更为严重。针对条形图SAR成像的FFBP退化问题，提出了一种基于SAR sinogram SD-FBP算法。分析了SD-FBP算法的复杂度，并与FFBP算法和笛卡尔因式BP算法（CFBP）进行了比较。利用哨兵1号、高分3号、芦滩1号等星载条带图SAR数据，验证了SD-FBP算法的优越性。结果表明，SD-FBP算法能够有效解决带状图SAR中FFBP算法的成像退化问题，并且比FFBP算法和CFBP算法运行速度更快。

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来源期刊

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 地学-成像科学与照相技术

CiteScore

9.30

自引率

10.90%

发文量

563

审稿时长

4.7 months

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.