Volume 8 Issue 3
Jun.  2019
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Article Navigation >  Journal of Radars  > 2019  >  8(3): 303-317
JIANG Qian, WU Hao, and WANG Yanyu. Airborne multi-functional maritime surveillance radar system design and key techniques[J]. Journal of Radars, 2019, 8(3): 303–317. doi: 10.12000/JR19045
Citation: JIANG Qian, WU Hao, and WANG Yanyu. Airborne multi-functional maritime surveillance radar system design and key techniques[J]. Journal of Radars, 2019, 8(3): 303–317. doi: 10.12000/JR19045
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Airborne Multi-functional Maritime Surveillance Radar System Design and Key Techniques

DOI: 10.12000/JR19045
  • ①.

    The 38th Research Institute of China Electronics Technology Group Corporation, Hefei 230088, China

  • ②.

    Key Laboratory of Aperture Array and Space Application, Hefei 230088, China

  • ③.

    Navy Military Representative Office in Hefei, Hefei 230088, China

More Information
  • Corresponding author: JIANG Qian, jiangqian0925@163.com
  • Received Date: 2019-03-19
  • Rev Recd Date: 2019-06-17
    • Available Online: 2019-06-24
  • Publish Date: 2019-06-01
    Abstract
  • As the main task load of the airborne platform for sea detection, the airborne multi-functional marine surveillance radar system has the following characteristics: the ability to operate in all weather conditions regularly, a wide detection range, and a complex and changeable working environment. Moreover, the system has a wide area coverage, great application prospects, and plays an important role in marine combat. According to the system characteristics and the advantages of the multi-functional marine surveillance radar, the selection of radar system, working parameters, and the working mode design of the system are discussed. The problems of slow target detection, ineffective tracking and target identification in strong sea clutter, which affects the key performance of the system, and technical ways to solve them are analyzed.

     

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  • [1]
    陈锋. 国外机载海面监视雷达发展现状与趋势[J]. 直升机技术, 2011(1): 64–68. doi: 10.3969/j.issn.1673-1220.2011.01.013

    CHEN Feng. Development of the abroad airborne maritime surveillance radar[J]. Helicopter Technique, 2011(1): 64–68. doi: 10.3969/j.issn.1673-1220.2011.01.013
    [2]
    刘亮, 吉波. 无人机载雷达现状及发展趋势[J]. 现代导航, 2014(3): 227–231.

    LIU Liang and JI Bo. Status and development of radar on UAV[J]. Modern Navigation, 2014(3): 227–231.
    [3]
    Raytheon Company. SeaVue radar introduction datasheet[EB/OL]. www.raytheon.com.
    [4]
    Thales Company. Ocean master radar introduction datasheet[EB/OL]. www.thales.com.
    [5]
    IAI Elta System Company. EL/M-2022U radar introduction datasheet[EB/OL]. www.elta-ia.icom.
    [6]
    SELEX GALILEO Company. Seaspray radar introduction datasheet[EB/OL]. www.leonardocompany.com.
    [7]
    张翼麟. 美国MQ-4C无人机发展特点及趋势分析[J]. 飞航导弹, 2014(1): 45–48.

    ZHANG Yilin. Analysis of the development characteristics and trend of american MQ-4C UAV[J]. Aerodynamic Missile Journal, 2014(1): 45–48.
    [8]
    陈祖香. 美国MQ-4C无人机基本性能及作战应用[J]. 飞航导弹, 2016(12): 16–21.

    CHEN Zuxiang. Basic performance and operational application of american MQ-4C UAV[J]. Aerodynamic Missile Journal, 2016(12): 16–21.
    [9]
    IPPOLITO L J. Propagation Effects Handbook for Satellite Systems Design[M]. 4th ed. Baltimore: NASA Reference Publication, 1989.
    [10]
    徐艳国, 李宗武. 高分辨率雷达的海杂波特性研究[J]. 现代雷达, 2008, 30(5): 17–20. doi: 10.3969/j.issn.1004-7859.2008.05.005

    XU Yanguo and LI Zongwu. A study on sea clutter characteristics of high resolution radar[J]. Modern Radar, 2008, 30(5): 17–20. doi: 10.3969/j.issn.1004-7859.2008.05.005
    [11]
    何友, 黄勇, 关键, 等. 海杂波中的雷达目标检测技术综述[J]. 现代雷达, 2014, 36(12): 1–9. doi: 10.3969/j.issn.1004-7859.2014.12.001

    HE You, HUANG Yong, GUAN Jian, et al. An overview on radar target detection in sea clutter[J]. Modern Radar, 2014, 36(12): 1–9. doi: 10.3969/j.issn.1004-7859.2014.12.001
    [12]
    王雪松. 雷达极化技术研究现状与展望[J]. 雷达学报, 2016, 5(2): 119–131. doi: 10.12000/JR16039

    WANG Xuesong. Status and prospects of radar polarimetry techniques[J]. Journal of Radars, 2016, 5(2): 119–131. doi: 10.12000/JR16039
    [13]
    赵春雷, 王亚梁, 阳云龙, 等. 雷达极化信息获取及极化信号处理技术研究综述[J]. 雷达学报, 2016, 5(6): 620–638. doi: 10.12000/JR16092

    ZHAO Chunlei, WANG Yaliang, YANG Yunlong, et al. Review of radar polarization information acquisition and polarimetric signal processing techniques[J]. Journal of Radars, 2016, 5(6): 620–638. doi: 10.12000/JR16092
    [14]
    王军东. 海杂波对机载雷达探测距离的影响[J]. 电子测量技术, 2018, 41(8): 21–24.

    WANG Jundong. Influence of sea clutter on airborne radar detection range[J]. Electronic Measurement Technology, 2018, 41(8): 21–24.
    [15]
    WARD K D, BAKER C J, and WATTS S. Maritime surveillance radar. I. Radar scattering from the ocean surface[J]. IEE Proceedings F - Radar and Signal Processing, 1990, 137(2): 51–62. doi: 10.1049/ip-f-2.1990.0009
    [16]
    RYAN J and JOHNSON M. Radar performance prediction for target detection at sea[C]. Proceedings of 1992 International Conference on Radar, Brighton, UK, 1992: 13–17.
    [17]
    CHAN H C. Radar sea-clutter at low grazing angles[J]. IEE Proceedings F- Radar and Signal Processing, 1990, 137(2): 102–112. doi: 10.1049/ip-f-2.1990.0015
    [18]
    丁昊, 董云龙, 刘宁波, 等. 海杂波特性认知研究进展与展望[J]. 雷达学报, 2016, 5(5): 499–516. doi: 10.12000/JR16069

    DING Hao, DONG Yunlong, LIU Ningbo, et al. Overview and prospects of research on sea clutter property cognition[J]. Journal of Radars, 2016, 5(5): 499–516. doi: 10.12000/JR16069
    [19]
    刘宁波, 关键, 黄勇, 等. 海杂波的分段分数布朗运动模型[J]. 物理学报, 2012, 61(19): 190503. doi: 10.7498/aps.61.190503

    LIU Ningbo, GUAN Jian, HUANG Yong, et al. Piecewise fractional Brownian motion for modeling sea clutter[J]. Acta Physica Sinica, 2012, 61(19): 190503. doi: 10.7498/aps.61.190503
    [20]
    谢洪森, 邹鲲, 周鹏. 低掠射角海杂波的统计特性分析[J]. 雷达科学与技术, 2011, 9(2): 172–179. doi: 10.3969/j.issn.1672-2337.2011.02.015

    XIE Hongsen, ZOU Kun, and ZHOU Peng. Statistical analysis of sea clutter at low grazing angle[J]. Radar Science and Technology, 2011, 9(2): 172–179. doi: 10.3969/j.issn.1672-2337.2011.02.015
    [21]
    陈小龙, 关键, 黄勇, 等. 雷达低可观测动目标精细化处理及应用[J]. 科技导报, 2017, 35(20): 19–27. doi: 10.3981/j.issn.1000-7857.2017.20.002

    CHEN Xiaolong, GUAN Jian, HUANG Yong, et al. Radar refined processing and its applications for low-observable moving target[J]. Science &Technology Review, 2017, 35(20): 19–27. doi: 10.3981/j.issn.1000-7857.2017.20.002
    [22]
    陈小龙, 关键, 何友, 等. 高分辨稀疏表示及其在雷达动目标检测中的应用[J]. 雷达学报, 2017, 6(3): 239–251. doi: 10.12000/JR16110

    CHEN Xiaolong, GUAN Jian, HE You, et al. High-resolution sparse representation and its applications in radar moving target detection[J]. Journal of Radars, 2017, 6(3): 239–251. doi: 10.12000/JR16110
    [23]
    舒占军. 基于高分辨距离像的雷达目标识别算法研究[D]. [硕士论文], 电子科技大学, 2016.

    SHU Zhanjun. Study on radar target recognttion using high resolution range profiles[D]. [Master dissertation], University of Electronic Science and Technology of China, 2016.
    [24]
    王燕宇, 党红杏, 张长耀. ISAR船只识别技术应用综述[C]. 第九届全国雷达学术年会论文集, 烟台, 2004: 640-643.

    WANG Yanyu, DANG Hongxing, and ZHANG Changyao. Overview of ISAR ship recognition technology application[C]. Proceedings of National Radar Academic Annual Conference, Yantai, China, 2004: 640–643.
    [25]
    陈文婷. SAR图像舰船目标特征提取与分类识别方法研究[D]. [硕士论文], 国防科学技术大学, 2012.

    CHEN Wenting. Study on the methods of feature extraction and recognition of ships in SAR imagery[D]. [Master dissertation], National University of Defense Technology, 2012.
    [26]
    邢相薇, 计科峰, 康利鸿, 等. HRWS SAR图像舰船目标监视技术研究综述[J]. 雷达学报, 2015, 4(1): 107–121. doi: 10.12000/JR14144

    XING Xiangwei, JI Kefeng, KANG Lihong, et al. Review of ship surveillance technologies based on high-resolution wide-swath synthetic aperture radar imaging[J]. Journal of Radars, 2015, 4(1): 107–121. doi: 10.12000/JR14144
    [27]
    陈文婷, 邢相薇, 计科峰. SAR图像舰船目标识别综述[J]. 现代雷达, 2012, 34(11): 53–58. doi: 10.3969/j.issn.1004-7859.2012.11.013

    CHEN Wenting, XING Xiangwei, and JI Kefeng. A survey of ship target recognition in SAR images[J]. Modern Radar, 2012, 34(11): 53–58. doi: 10.3969/j.issn.1004-7859.2012.11.013
    [28]
    王庆, 廖静娟, 田帮森. 基于特征值分解的全极化SAR遥感数据分类研究[J]. 遥感技术与应用, 2010, 25(1): 31–37. doi: 10.11873/j.issn.1004-0323.2010.1.31

    WANG Qing, LIAO Jingjuan, and TIAN Bangsen. Polarimetric SAR data classification with eigenvalue-based decompositions[J]. Remote Sensing Technology and Application, 2010, 25(1): 31–37. doi: 10.11873/j.issn.1004-0323.2010.1.31
    [29]
    刘眉洁, 戴永寿, 张杰, 等. 高分辨率全极化合成孔径雷达数据海冰二次分类方法研究[J]. 海洋学报, 2013, 35(4): 80–87. doi: 10.3969/j.issn.0253-4193.2013.04.010

    LIU Meijie, DAI Yongshou, ZHANG Jie, et al. The research on the object-based method of sea ice classification of high-resolution quad-polarization SAR data[J]. Acta Oceanologica Sinica, 2013, 35(4): 80–87. doi: 10.3969/j.issn.0253-4193.2013.04.010
    [30]
    安彧. 海战场舰船目标检测与识别研究[D]. [博士论文], 2015: 59–80.

    Anbiao. Research on ship target detection and recognition in sea battlefield [D]. [Ph.D. dissertation], Harbin Engineering University, 2015: 59–80.
    [31]
    承德保, 胡风明, 杨汝良. 利用改进分形特征对SAR图像目标检测方法的研究[J]. 电子与信息学报, 2009, 31(1): 164–168. doi: 10.3724/SP.J.1146.2008.00416

    CHENG Debao, HU Fengming, and YANG Ruliang. Study on target detection of SAR image using improved fractal feature[J]. Journal of Electronics &Information Technology, 2009, 31(1): 164–168. doi: 10.3724/SP.J.1146.2008.00416
    [32]
    吴义兵, 宋建社, 王瑞花. 基于分形维数的SAR图像纹理特征的提取[J]. 四川兵工学报, 2011, 32(7): 74–77, 84.

    WU Yibing, SONG Jianshe, and WANG Ruihua. Extraction of texture features of SAR images based on fractal dimension[J]. Journal of Sichuan Ordnance, 2011, 32(7): 74–77, 84.
    [33]
    LEE W L and HSIEH K S. A robust algorithm for the fractal dimension of images and its applications to the classification of natural images and ultrasonic liver images[J]. Signal Processing, 2010, 90(6): 1894–1904. doi: 10.1016/j.sigpro.2009.12.010
    [34]
    蒋少峰, 王超, 吴樊, 等. 基于结构特征分析的COSMO-SkyMed图像商用船舶分类算法[J]. 遥感技术与应用, 2014, 29(4): 607–615. doi: 10.11873/j.issn.1004-0323.2014.4.0607

    JIANG Shaofeng, WANG Chao, WU Fan, et al. Algorithm for merchant ship classification in COSMO-SkyMed images based on structural feature analysis[J]. Remote Sensing Technology and Application, 2014, 29(4): 607–615. doi: 10.11873/j.issn.1004-0323.2014.4.0607
    [35]
    张华俊. 基于图像特征匹配技术的数字图像相关法研究[D]. [硕士论文], 安徽大学, 2014.

    ZHANG Huajun. Research of digital image correlation method based on image feature matching technology[D]. [Master dissertation], Anhui University, 2014.
    [36]
    CHEN Wenting, JI Kefeng, XING Xiangwei, et al. Ship recognition in high resolution SAR imagery based on feature selection[C]. Proceedings of International Conference on Computer Vision in Remote Sensing, Xiamen, China, 2013.
    [37]
    蒋少峰. 高分辨率SAR图像船舶检测与分类方法研究[D]. [硕士论文], 中国科学院大学, 2013.

    JIANG Shaofeng. Study of ship detection and classification in high resolution SAR image[D]. [Master dissertation], University of Chinese Academy of Sciences, 2013.
    [38]
    孙勋, 黄平平, 涂尚坦, 等. 利用多特征融合和集成学习的极化SAR图像分类[J]. 雷达学报, 2016, 5(6): 692–700. doi: 10.12000/JR15132

    SUN Xun, HUANG Pingping, TU Shangtan, et al. Polarimetric SAR image classification using multiple-feature fusion and ensemble learning[J]. Journal of Radars, 2016, 5(6): 692–700. doi: 10.12000/JR15132
    [39]
    王俊, 郑彤, 雷鹏, 等. 深度学习在雷达中的研究综述[J]. 雷达学报, 2018, 7(4): 395–411. doi: 10.12000/JR18040

    WANG Jun, ZHENG Tong, LEI Peng, et al. Study on deep learning in radar[J]. Journal of Radars, 2018, 7(4): 395–411. doi: 10.12000/JR18040
    [40]
    苏宁远, 陈小龙, 关键, 等. 基于卷积神经网络的海上微动目标检测与分类方法[J]. 雷达学报, 2018, 7(5): 565–574. doi: 10.12000/JR18077

    SU Ningyuan, CHEN Xiaolong, GUAN Jian, et al. Detection and classification of maritime target with micro-motion based on CNNs[J]. Journal of Radars, 2018, 7(5): 565–574. doi: 10.12000/JR18077
    [41]
    贺丰收, 张涛, 芦达. 机载对海探测雷达发展趋势[J]. 科技导报, 2017, 35(20): 28–35. doi: 10.3981/j.issn.1000-7857.2017.20.003

    HE Fengshou, ZHANG Tao, and LU da. Progress of airborne maritime detection radar[J]. Science &Technology Review, 2017, 35(20): 28–35. doi: 10.3981/j.issn.1000-7857.2017.20.003
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