Volume 10 Issue 3
Jun.  2021
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ZENG Tao, WEN Yuhan, WANG Yan, et al. Research progress on synthetic aperture radar parametric imaging methods[J]. Journal of Radars, 2021, 10(3): 327–341. doi: 10.12000/JR21004
Citation: ZENG Tao, WEN Yuhan, WANG Yan, et al. Research progress on synthetic aperture radar parametric imaging methods[J]. Journal of Radars, 2021, 10(3): 327–341. doi: 10.12000/JR21004

Research Progress on Synthetic Aperture Radar Parametric Imaging Methods(in English)

DOI: 10.12000/JR21004
Funds:  The National Science Fund for Distinguished Young Scholars (61625103), The Beijing Natural Science Foundation (4202067), The National Natural Science Foundation of China (11833001, 61931002)
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  • Corresponding author: WANG Yan, yan_wang@bit.edu.cn
  • Received Date: 2021-01-11
  • Rev Recd Date: 2021-03-21
  • Publish Date: 2021-04-12
  • Under the constraints of the point scattering model, traditional Synthetic Aperture Radar (SAR) imaging algorithms can be regarded as a mapping from data space to image space. However, most objects in the real scene are extended targets, which are mismatched with the point scattering model in traditional linear imaging algorithms. The abovementioned reasons lead to the distortion of SAR image representation. A common phenomenon is that the extended targets appear as isolated scattered points, which hinder the application of target recognition on the basis of SAR images. SAR parametric nonlinear imaging techniques are established to solve the abovementioned model mismatch problem. Such methods are characterized by the scattering models that consider point targets and extended targets. Specifically, by using the sensitivity of the phase and amplitude characteristics of the echoes or images to the observation angles, SAR parametric imaging methods can first identify the target type and estimate the scattering parameters, and then reconstruct the target image on the basis of the scattering model. SAR parametric imaging methods can obtain better image quality than traditional linear methods for extended targets. This article mainly introduces the parametric imaging methods of linear extended targets, which correspond to the isolated strong points and continuous edges of objects in the real scene, and discusses the parametric imaging methods on the basis of the echo and image domains and experimental results. Last, the future development trends of SAR parametric imaging methods are discussed.

     

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  • [1]
    Air Force Research Laboratory Sensor Data Management System. Backhoe data sample and visual-d challenge problem[EB/OL]. https://www.sdms.afrl.af.mil, 2004.
    [2]
    李春升, 杨威, 王鹏波. 星载SAR成像处理算法综述[J]. 雷达学报, 2013, 2(1): 111–122. doi: 10.3724/SP.J.1300.2013.20071

    LI Chunsheng, YANG Wei, and WANG Pengbo. A review of spaceborne SAR algorithm for image formation[J]. Journal of Radars, 2013, 2(1): 111–122. doi: 10.3724/SP.J.1300.2013.20071
    [3]
    MCCORKLE J W and ROFHEART M. An order N2log(N) backprojector algorithm for focusing wide-angle wide-bandwidth arbitrary-motion synthetic aperture radar[C]. Proceedings Volume 2747, Radar Sensor Technology, Orlando, USA, 1996: 25–36.
    [4]
    CUMMING I G and WONG F H. Digital Processing of Synthetic Aperture Radar Imaging Algorithm and Implementation[M]. Beijing: Electronic Industries Press, 2007: 155–191.
    [5]
    BREIT H, SCHATTLER B, and STEINBRECHER U. A high precision workstation-based chirp scaling SAR processor[C]. The IEEE International Geoscience and Remote Sensing Symposium, Remote Sensing - A Scientific Vision for Sustainable Development, Singapore, 1997: 465–467.
    [6]
    DAI Eryan, JIN Yaqiu, HAMASAKI T, et al. Three-dimensional stereo reconstruction of buildings using polarimetric SAR images acquired in opposite directions[J]. IEEE Geoscience and Remote Sensing Letters, 2008, 5(2): 236–240. doi: 10.1109/LGRS.2008.915744
    [7]
    XU Feng and JIN Yaqiu. Automatic reconstruction of building objects from multiaspect meter-resolution SAR images[J]. IEEE Transactions on Geoscience and Remote Sensing, 2007, 45(7): 2336–2353. doi: 10.1109/TGRS.2007.896614
    [8]
    SCHMITT A. Multiscale and multidirectional multilooking for SAR image enhancement[J]. IEEE Transactions on Geoscience and Remote Sensing, 2016, 54(9): 5117–5134. doi: 10.1109/TGRS.2016.2555624
    [9]
    ISHIMARU A, CHAN T K, and KUGA Y. An imaging technique using confocal circular synthetic aperture radar[J]. IEEE Transactions on Geoscience and Remote Sensing, 1998, 36(5): 1524–1530. doi: 10.1109/36.718856
    [10]
    SOUMEKH M. Reconnaissance with slant plane circular SAR imaging[J]. IEEE Transactions on Image Processing, 1996, 5(8): 1252–1265. doi: 10.1109/83.506760
    [11]
    POHL C and VAN GENDEREN J L. Review article multisensor image fusion in remote sensing: Concepts, methods and applications[J]. International Journal of Remote Sensing, 1998, 19(5): 823–854. doi: 10.1080/014311698215748
    [12]
    BYUN Y, CHOI J, and HAN Y. An area-based image fusion scheme for the integration of SAR and optical satellite imagery[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2013, 6(5): 2212–2220. doi: 10.1109/JSTARS.2013.2272773
    [13]
    徐建平, 皮亦鸣, 曹宗杰. 基于贝叶斯压缩感知的合成孔径雷达高分辨成像[J]. 电子与信息学报, 2011, 33(12): 2863–2868. doi: 10.3724/SP.J.1146.2010.01377

    XU Jianping, PI Yiming, and CAO Zongjie. SAR imaging based on Bayesian compressive sensing[J]. Journal of Electronics&Information Technology, 2011, 33(12): 2863–2868. doi: 10.3724/SP.J.1146.2010.01377
    [14]
    JI Shihao, XUE Ya, and CARIN L. Bayesian compressive sensing[J]. IEEE Transactions on Signal Processing, 2008, 56(6): 2346–2356. doi: 10.1109/tsp.2007.914345
    [15]
    YANG Jungang, THOMPSON J, HUANG Xiaotao, et al. Random-frequency SAR imaging based on compressed sensing[J]. IEEE Transactions on Geoscience and Remote Sensing, 2013, 51(2): 983–994. doi: 10.1109/TGRS.2012.2204891
    [16]
    卫扬铠, 曾涛, 陈新亮, 等. 典型线面目标合成孔径雷达参数化成像[J]. 雷达学报, 2020, 9(1): 143–153. doi: 10.12000/JR19077

    WEI Yangkai, ZENG Tao, CHEN Xinliang, et al. Parametric SAR imaging for typical lines and surfaces[J]. Journal of Radars, 2020, 9(1): 143–153. doi: 10.12000/JR19077
    [17]
    ZENG Tao, WEI Yangkai, DING Zegang, et al. Parametric image reconstruction for edge recovery from synthetic aperture radar echoes[J]. IEEE Transactions on Geoscience and Remote Sensing, 2021, 59(3): 2155–2173. doi: 10.1109/TGRS.2020.3006884
    [18]
    WEN Yuhan, WANG Yan, DING Zegang, et al. Parametric synthetic aperture radar image recovery for multiple linear structures: An image domain approach[J]. Remote Sensing, 2020, 12(12): 1996. doi: 10.3390/rs12121996
    [19]
    贺思三. 雷达成像中的非理想散射现象分析[D]. [硕士论文], 国防科学技术大学, 2005: 16–24.

    HE Sisan. Analysis of non-ideal scattering phenomenon in radar imaging[D]. [Master dissertation], National University of Defense Technology, 2005: 16–24.
    [20]
    TAKET N D and BURGE R E. A physical optics version of the geometrical theory of diffraction[J]. IEEE Transactions on Antennas and Propagation, 1991, 39(6): 719–731. doi: 10.1109/8.86868
    [21]
    JACKSON J A, RIGLING B D, and MOSES R L. Canonical scattering feature models for 3D and bistatic SAR[J]. IEEE Transactions on Aerospace and Electronic Systems, 2010, 46(2): 525–541. doi: 10.1109/TAES.2010.5461639
    [22]
    FAN Yujie, CHEN Xinliang, WEI Yangkai, et al. The distributed SAR imaging method for cylinder target[C]. IEEE International Geoscience and Remote Sensing Symposium, Yokohama, Japan, 2019: 2921–2924. doi: 10.1109/IGARSS.2019.8898372
    [23]
    范宇杰, 温育涵, 卫扬铠, 等. 连续目标双基地调频连续波SAR回波建模方法[J]. 信号处理, 2018, 34(11): 1345–1354. doi: 10.16798/j.issn.1003-0530.2018.11.010

    FAN Yujie, WEN Yuhan, WEI Yangkai, et al. Continuous target bistatic FMCW SAR echo modeling method[J]. Journal of Signal Processing, 2018, 34(11): 1345–1354. doi: 10.16798/j.issn.1003-0530.2018.11.010
    [24]
    BHALLA R, MOORE J, and LING Hao. A global scattering center representation of complex targets using the shooting and bouncing ray technique[J]. IEEE Transactions on Antennas and Propagation, 1997, 45(12): 1850–1856. doi: 10.1109/8.650204
    [25]
    POTTER L C and MOSES R L. Attributed scattering centers for SAR ATR[J]. IEEE Transactions on Image Processing, 1997, 6(1): 79–91. doi: 10.1109/83.552098
    [26]
    MA Conghui, WEN Gongjian, DING Boyuan, et al. Three-dimensional electromagnetic model-based scattering center matching method for synthetic aperture radar automatic target recognition by combining spatial and attributed information[J]. Journal of Applied Remote Sensing, 2016, 10(1): 016025. doi: 10.1117/1.JRS.10.016025
    [27]
    DING Baiyuan and WEN Gongjian. Target reconstruction based on 3-D scattering center model for robust SAR ATR[J]. IEEE Transactions on Geoscience and Remote Sensing, 2018, 56(7): 3772–3785. doi: 10.1109/TGRS.2018.2810181
    [28]
    AMERICA C O. CST studio suite 2011: Integrating simulation technology[J]. Microwave Journal, 2010, 53(12): 92–96.
    [29]
    GERRY M J, POTTER L C, GUPTA I J, et al. A parametric model for synthetic aperture radar measurements[J]. IEEE Transactions on Antennas and Propagation, 1999, 47(7): 1179–1188. doi: 10.1109/8.785750
    [30]
    GAO Yuexin, XING Mengdao, GUO Liang, et al. Extraction of anisotropic characteristics of scattering centers and feature enhancement in wide-angle SAR imagery based on the iterative re-weighted tikhonov regularization[J]. Remote Sensing, 2018, 10(12): 2066. doi: 10.3390/rs10122066
    [31]
    高悦欣, 李震宇, 盛佳恋, 等. 一种大转角SAR图像散射中心各向异性提取方法[J]. 电子与信息学报, 2016, 38(8): 1956–1961. doi: 10.11999/JEIT151261

    GAO Yuexin, LI Zhenyu, SHENG Jialian, et al. Extraction method for anisotropy characteristic of scattering center in wide-angle SAR imagery[J]. Journal of Electronics&Information Technology, 2016, 38(8): 1956–1961. doi: 10.11999/JEIT151261
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