Volume 8 Issue 5
Oct.  2019
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Article Navigation >  Journal of Radars  > 2019  >  8(5): 606-615
JIANG Wen and LI Wangzhe. A new method for parameter estimation of attributed scattering centers based on amplitude-phase separation[J]. Journal of Radars, 2019, 8(5): 606–615. doi: 10.12000/JR18097
Citation: JIANG Wen and LI Wangzhe. A new method for parameter estimation of attributed scattering centers based on amplitude-phase separation[J]. Journal of Radars, 2019, 8(5): 606–615. doi: 10.12000/JR18097
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A New Method for Parameter Estimation of Attributed Scattering Centers Based on Amplitude-phase Separation

doi: 10.12000/JR18097

  • National Key Lab of Microwave Imaging Technology, Beijing 100190, China

  • Institute of Electronics Chinese Academy of Sciences, Beijing 100190, China

  • University of Chinese Academy of Sciences, Beijing 100049, China

Funds:  The National Natural Science Foundation of China (61701476, 61690191)
More Information
  • Corresponding author: LI Wangzhe, wzli@mail.ie.ac.cn
  • Received Date: 2018-11-15
  • Rev Recd Date: 2019-04-09
    • Available Online: 2019-06-28
  • Publish Date: 2019-10-01
    Abstract
  • Parameter estimation of Attributed Scattering Centers (ASCs) corresponding to scattering geometries on targets plays an important role in Synthetic Aperture Radar (SAR) imaging-assisted Automatic Target Recognition (ATR). To achieve computational savings and clutter suppression, we extract the measurements of several ASCs and estimate the parameters of each ASC separately. To improve the speed of the estimation process, we propose a method for parameter estimation of ASCs based on amplitude–phase separation that considers a reasonable assumption that the amplitude- and phase-related parameters of an ASC can be estimated separately and independently. Through the proposed method, the complexity and time consumed for parameter estimation are reduced by one order of magnitude than the traditional method. The Iterative Half Thresholding (IHT) algorithm is introduced to enhance the accuracy of parameter estimation. The types and locations of scattering geometries on the target are determined using the estimated ASC parameters. Using simulated data, measured data, and MSTAR data sets, the accuracy and efficiency of parameter estimation are improved and the effectiveness of the proposed method is verified.

     

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    • References(27)
  • [1]
    钟金荣. 目标三维电磁散射参数化模型反演方法研究[D]. [博士论文], 国防科学技术大学, 2016: 1–7.

    ZHONG Jinrong. Inverse methods for three dimensional parametric scattering model of target[D]. [Ph.D. dissertation], National University of Defense Technology, 2016: 1–7.
    [2]
    FRIEDLANDER R D, LEVY M, SUDKAMP E, et al. Deep learning model-based algorithm for SAR ATR[C]. Proceedings of Algorithms for Synthetic Aperture Radar Imagery XXV, Orlando, United States, 2018: 106470B. doi: 10.1117/12.2315265.
    [3]
    PEI Jifang, HUANG Yulin, HUO Weibo, et al. SAR automatic target recognition based on multiview deep learning framework[J]. IEEE Transactions on Geoscience and Remote Sensing, 2018, 56(4): 2196–2210. doi: 10.1109/TGRS.2017.2776357
    [4]
    ZHAO Pengfei, LIU Kai, ZOU Hao, et al. Multi-stream convolutional neural network for SAR automatic target recognition[J]. Remote Sensing, 2018, 10(9): 1473. doi: 10.3390/rs10091473
    [5]
    DUAN Jia, ZHANG Lei, XING Mengdao, et al. Polarimetric target decomposition based on attributed scattering center model for synthetic aperture radar targets[J]. IEEE Geoscience and Remote Sensing Letters, 2014, 11(12): 2095–2099. doi: 10.1109/lgrs.2014.2320053
    [6]
    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
    [7]
    文贡坚, 朱国强, 殷红成, 等. 基于三维电磁散射参数化模型的SAR目标识别方法[J]. 雷达学报, 2017, 6(2): 115–135. doi: 10.12000/JR17034

    WEN Gongjian, ZHU Guoqiang, YIN Hongcheng, et al. SAR ATR based on 3D parametric electromagnetic scattering model[J]. Journal of Radars, 2017, 6(2): 115–135. doi: 10.12000/JR17034
    [8]
    张亚军. 基于属性散射中心模型的SAR自动目标识别[D]. [硕士论文], 西安电子科技大学, 2014: 5–23.

    ZHANG Yajun. SAR automatic target recognition based on attributed scattering center models[D]. [Master dissertation], Xidian University, 2014: 5–23.
    [9]
    AKYILDIZ Y and MOSES R L. Scattering center model for SAR imagery[C]. Proceedings of SPIE 3869, SAR Image Analysis, Modeling, and Techniques II, Florence, Italy, 1999: 76–85. doi: 10.1117/12.373151.
    [10]
    CHIANG H C, MOSES R L, and POTTER L C. Model-based classification of radar images[J]. IEEE Transactions on Information Theory, 2000, 46(5): 1842–1854. doi: 10.1109/18.857795
    [11]
    DING Baiyuan, WEN Gongjian, HUANG Xiaohong, et al. Target recognition in synthetic aperture radar images via matching of attributed scattering centers[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2017, 10(7): 3334–3347. doi: 10.1109/JSTARS.2017.2671919
    [12]
    DING Baiyuan, WEN Gongjian, ZHONG Jinrong, et al. A robust similarity measure for attributed scattering center sets with application to SAR ATR[J]. Neurocomputing, 2017, 219: 130–143. doi: 10.1016/j.neucom.2016.09.007
    [13]
    段佳, 张磊, 盛佳恋, 等. 独立属性散射中心参数降耦合估计方法[J]. 电子与信息学报, 2012, 34(8): 1853–1859. doi: 10.3724/SP.J.1146.2011.01302

    DUAN Jia, ZHANG Lei, SHENG Jialian, et al. Parameters decouple and estimation of independent attributed scattering centers[J]. Journal of Electronics &Information Technology, 2012, 34(8): 1853–1859. doi: 10.3724/SP.J.1146.2011.01302
    [14]
    段佳, 张磊, 邢孟道, 等. 合成孔径雷达目标特征提取新方法[J]. 西安电子科技大学学报: 自然科学版, 2014, 41(4): 13–19. doi: 10.3969/j.issn.1001-2400.2014.04.003

    DUAN Jia, ZHANG Lei, XING Mengdao, et al. Novel feature extraction method for synthetic aperture radar targets[J]. Journal of Xidian University, 2014, 41(4): 13–19. doi: 10.3969/j.issn.1001-2400.2014.04.003
    [15]
    海鸿璋. 基于ISAR图像的舰船目标特征提取方法研究[D]. [硕士论文], 西安电子科技大学, 2014: 44–49.

    HAI Hongzhang. Study on feature extraction of ships based on ISAR images[D]. [Master dissertation], Xidian University, 2014: 44–49.
    [16]
    李飞, 纠博, 刘宏伟, 等. 基于稀疏表示的SAR图像属性散射中心参数估计算法[J]. 电子与信息学报, 2014, 36(4): 931–937. doi: 10.3724/SP.J.1146.2013.00576

    LI Fei, JIU Bo, LIU Hongwei, et al. Sparse representation based algorithm for estimation of attributed scattering center parameter on SAR imagery[J]. Journal of Electronics & Information Technology, 2014, 36(4): 931–937. doi: 10.3724/SP.J.1146.2013.00576
    [17]
    李飞. 雷达图像目标特征提取方法研究[D]. [博士论文], 西安电子科技大学, 2014: 50–66.

    LI Fei. Study on target feature extraction based on radar image[D]. [Ph.D. dissertation], Xidian University, 2014: 50–66.
    [18]
    LIU Hongwei, JIU Bo, LI Fei, et al. Attributed scattering center extraction algorithm based on sparse representation with dictionary refinement[J]. IEEE Transactions on Antennas and Propagation, 2017, 65(5): 2604–2614. doi: 10.1109/TAP.2017.2673764
    [19]
    苏伍各. 基于稀疏贝叶斯重构方法的雷达成像技术研究[D]. [博士论文], 国防科学技术大学, 2015: 3–14.

    SU Wuge. Radar imaging techiniques based on sparse Bayesian reconstruction methods[D]. [Ph.D. dissertation], National University of Defense Technology, 2015: 3–14.
    [20]
    LI Zenghui, JIN Kan, XU Bin, et al. An improved attributed scattering model optimized by incremental sparse Bayesian learning[J]. IEEE Transactions on Geoscience and Remote Sensing, 2016, 54(5): 2973–2987. doi: 10.1109/TGRS.2015.2509539
    [21]
    XU Zongben. Data Modeling: Visual Psychology Approach and L1/2 Regularization Theory[M]. BHATIA R, PAL A, RANGARAJAN G, et al. Proceedings of the International Congress of Mathematicians. Hyderabad, India: World Scientific, 2010: 3151–3184. doi: 10.1142/9789814324359_0184.
    [22]
    徐宗本, 吴一戎, 张冰尘, 等. 基于L1/2正则化理论的稀疏雷达成像[J]. 科学通报, 2018, 63(14): 1307–1319. doi: 10.1360/N972018-00372

    XU Zongben, WU Yirong, ZHANG Bingchen, et al. Sparse radar imaging based on L1/2 regularization theory[J]. Chinese Science Bulletin, 2018, 63(14): 1307–1319. doi: 10.1360/N972018-00372
    [23]
    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
    [24]
    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
    [25]
    KELLER J B. Geometrical theory of diffraction[J]. Journal of the Optical Society of America, 1962, 52(2): 116–130. doi: 10.1364/JOSA.52.000116
    [26]
    ÇETİN M. Feature-enhanced synthetic aperture radar imaging[D]. [Ph.D. dissertation], Boston University, 2001.
    [27]
    清风亦客. T-72主战坦克[EB/OL]. https://baike.baidu.com/item/T-72主战坦克/2031530?fr=aladdin, 2019.

    Qing Fengyike. T-72 main battle tank[EB/OL]. https://baike.baidu.com/item/T-72主战坦克/2031530?fr=aladdin, 2019.
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