合成孔径雷达抗干扰技术综述

黄岩 赵博 陶明亮 陈展野 洪伟

黄岩, 赵博, 陶明亮, 等. 合成孔径雷达抗干扰技术综述[J]. 雷达学报, 2020, 9(1): 86–106. doi: 10.12000/JR19113
引用本文: 黄岩, 赵博, 陶明亮, 等. 合成孔径雷达抗干扰技术综述[J]. 雷达学报, 2020, 9(1): 86–106. doi: 10.12000/JR19113
HUANG Yan, ZHAO Bo, TAO Mingliang, et al. Review of synthetic aperture radar interference suppression[J]. Journal of Radars, 2020, 9(1): 86–106. doi: 10.12000/JR19113
Citation: HUANG Yan, ZHAO Bo, TAO Mingliang, et al. Review of synthetic aperture radar interference suppression[J]. Journal of Radars, 2020, 9(1): 86–106. doi: 10.12000/JR19113

合成孔径雷达抗干扰技术综述

doi: 10.12000/JR19113
基金项目: 国家自然科学基金(61901112, 61801297, 61801390),十三五领域基金(61404130223),江苏省自然科学基金(BK20190330),深圳大学科研启动项目(2019119)
详细信息
    作者简介:

    黄岩:黄 岩(1991–),男,山东济南人,博士,讲师。2018年毕业于西安电子科技大学雷达信号处理国防科技重点实验室,获得信号与信息处理工学博士学位,现任东南大学信息科学与工程学院毫米波国家重点实验室讲师。主要研究方向为合成孔径雷达和MIMO雷达抗干扰技术、图像处理及解译、机器学习、目标检测与识别等。目前主持多项国家自然科学基金、军委科技委等雷达抗干扰技术相关的纵向课题。E-mail: yan_huang@seu.edu.cn

    赵博:赵 博(1986–),男,河南南阳人,博士,助理教授。2015年毕业于西安电子科技大学雷达信号处理重点实验室,获得信号与信息处理专业博士学位。2015–2018年在深圳大学从事博士后研究工作,2016–2017年为美国佛罗里达大学访问学者。现为深圳大学电子与信息工程学院助理教授。研究方向包括雷达系统设计、雷达信号处理、高分辨遥感探测、电子对抗、压缩采样与信息恢复等。E-mail: b_zhao@szu.edu.cn

    陶明亮(1989–),男,湖南株洲人,博士,副教授。2016年获西安电子科技大学工学博士学位,现任西北工业大学电子信息学院副教授。陕西省优秀博士学位论文和首届中国电子教育学会优秀博士论文获得者,2017年入选全国博士后创新人才支持计划,并获国际无线电科学联盟颁发的“青年科学家奖”,2018年入选陕西省青年科技新星和陕西省高校科协青年托举人才支持计划。主要研究方向为复杂电磁环境对抗技术。E-mail: mltao@nwpu.edu.cn

    陈展野(1993–),男,湖北黄冈人,博士,讲师。2019年在西安电子科技大学雷达信号处理国家重点实验室获得博士学位,现担任重庆大学微电子与通信工程学院讲师。主要研究方向为合成孔径雷达信号处理,地/海面运动目标检测。E-mail: czy@cqu.edu.cn

    洪伟:洪 伟(1962–),男,教授,博士生导师。1988年在东南大学无线电工程系(现信息科学与工程学院)获得博士学位,现任东南大学信息科学与工程学院毫米波国家重点实验室主任,教育部长江学者计划特聘教授,IEEE Fellow, CIE Fellow,国家杰出青年基金获得者。主要研究方向为电磁场与微波技术、毫米波亚毫米波理论与技术、无线通信射频与天线技术。作为首席科学家或项目负责人承担完成多项国家973、863、创新群体、科技重大专项项目等。获国家自然科学二等奖、四等奖各1项,部省科技进步一等奖3项等多项科技奖以及IEEE 802.11aj国际标准杰出贡献奖、首届全国创新争先奖状等。E-mail: weihong@seu.edu.cn

    通讯作者:

    黄岩 yan_huang@seu.edu.cn

  • 1 文中所述的压制干扰包含射频干扰等无意压制干扰,由于其干扰模型和效果均与窄带压制干扰类似,后文就一并讨论。
  • 中图分类号: TN974

Review of Synthetic Aperture Radar Interference Suppression

Funds: The National Natural Science Foundation of China (61901112, 61801297, 61801390), The Advanced Research Foundation (61404130223), The Natural Science Foundation of Jiangsu Province (BK20190330), Shenzhen University Foundation (2019119)
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  • 摘要: 合成孔径雷达(SAR)得益于其全天时全天候、高分辨率的工作模式,在最近几十年吸引了全球雷达学者的目光。作为一种有源雷达系统,合成孔径雷达高分辨成像过程中会受多样式复杂多变的强电磁干扰影响,从而严重影响合成孔径雷达最终的高分辨成像结果,因此,如何有效对抗复杂电磁干扰是合成孔径雷达探测感知的难点和重点之一。该文针对不同的干扰样式、干扰来源、干扰散射机理、雷达天线配置、目标特性等合成孔径雷达抗干扰及高分辨成像的关键要素和主要思路进行了总结梳理,并依照干扰对抗算法的本质,对近些年代表性的合成孔径雷达对抗压制干扰和欺骗干扰算法的文献进行介绍和归纳,旨在为以后的研究提供一定的参考。

     

  • 图  1  窄带射频干扰对合成孔径雷达成像的影响

    Figure  1.  Effect of narrowband RFI to SAR imaging

    图  2  欺骗干扰对合成孔径雷达成像的影响

    Figure  2.  Effect of deceptive jamming to SAR imaging

    图  3  合成孔径雷达有源干扰分类

    Figure  3.  Classification of sourced interferences for SAR systems

    图  4  不同维度的窄带、宽带压制干扰信号模型示意图

    Figure  4.  Illustrations of narrowband and wideband suppressed interference models in different domains

    图  5  欺骗干扰和真实回波的时频分布模型示意图

    Figure  5.  Illustration of the time-frequency distribution of deceptive jammings and true echoes

    图  6  PALSAR实测数据陷波滤波器干扰抑制性能[40]

    Figure  6.  Interference suppression performance of the notched filter on PALSAR real data[40]

    图  7  后验陷波滤波方法流程图[44]

    Figure  7.  Block diagram of Posteriori Notched Filtering[44]

    图  8  ALOS PALSAR实测数据验证时域最小均方滤波器抑制干扰性能[56]

    Figure  8.  Interference suppression performance of TDLMS filter on ALOS PALSAR real data[56]

    图  9  维纳滤波在低频直升机载合成孔径雷达系统对抗窄带射频干扰[62]

    Figure  9.  Narrowband RFI suppression performance of Wiener filter on the Helicopter-borne SAR system[62]

    图  10  实测合成孔径雷达场景下特征子空间投影方法与陷波滤波器抗干扰性能对比[63]

    Figure  10.  Performance comparison of ESP method and notched filter[63]

    图  11  宽带干扰下子空间投影法与陷波滤波器的2维距离时频谱对比[67]

    Figure  11.  Performance comparison of the ESP method and notched filters for wideband interference[67]

    图  12  IAA方法迭代估计窄带干扰正弦信号参数[71]

    Figure  12.  Narrowband interference sinusoidal parameter estimation with IAA method[71]

    图  13  美国陆军研究实验室的稀疏恢复半参数化方法抑制射频干扰[76]

    Figure  13.  Sparse recovery semi-parametric method for RFI suppression by US Army Research Lab[76]

    图  14  张量理论半参数化干扰抑制方法性能[88]

    Figure  14.  Performance of tensor theory semi-parametric interference suppression method[88]

    图  15  多通道直达波欺骗干扰抑制效果[92]

    Figure  15.  Direct-path deceptive jamming suppression performance[92]

    图  16  仿真数据快时间STAP的欺骗干扰抑制性能对比原始图像[92]

    Figure  16.  Fast-time STAP deceptive jamming suppression performance via simulated data[92]

    图  17  单通道合成孔径雷达系统复杂场景欺骗干扰辨识效果[103]

    Figure  17.  Deceptive scene recognition for single-channel SAR system[103]

    图  18  单通道合成孔径雷达欺骗干扰污染场景重构结果[107]

    Figure  18.  Reconstruction of the deceptive jamming polluted scene for single channel SAR system[107]

    表  1  现有抗单一类型孤立干扰方法优缺点对比(*表示最优)

    Table  1.   Comparison of isolated interference suppression methods (* denotes optimal)

    非参数化方法参数化方法半参数化方法
    计算复杂度*较高
    性能较差*
    真实信号保护项*
    参数*有(模型参数)有(超参数)
    性能依赖条件干扰足够强干扰模型已知超参数、优化模型
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  • 收稿日期:  2019-12-17
  • 修回日期:  2020-02-15
  • 网络出版日期:  2020-03-11
  • 刊出日期:  2020-02-28

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