分数阶傅里叶和压缩感知自适应抗频谱弥散干扰
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摘要
频谱弥散(SMSP)干扰与线性调频雷达信号之间存在大量的时频域耦合,干扰效能突出。该文提出一种信息域的抗SMSP干扰的信号处理算法,根据SMSP干扰信号的形式与特点,通过自适应改变压缩感知的干扰基字典,同时匹配雷达信号与干扰信号的调频率,构建压缩感知求解模型并基于凸优化算法完成信号重构,最终实现干扰信号的识别及雷达信号的提取。该算法中冗余字典的构造采用了Pei型分数阶傅里叶快速分解方法,不需要反复对信号进行时频域解耦,并且迭代次数较少,运算效率较高。
SMeared SPectrum(SMSP) jamming has lots of coupling in time and frequency domain with Linear Frequency Modulated(LFM) radar signals, which has good jamming performance. This paper proposes a signal processing method for countering SMSP jamming in information domain. According to the formulation and characteristics of SMSP signal, the jamming dictionary is changed automatically, the frequency modulation rate of LFM and SMSP signal is matcheal at the same time, the compressed sampling model is consructed and reconstruction of signal is carried out based on convex optimization. Finally, the recognition of jamming signal and extraction of radar signal are achieved. Pei type fractional Fourier decomposition method is used in construction of redundant dictionary. Modulation and demodulation between time and frequency domain are avoided in this method, which leads to improvement in fewer iteration times and higher arithmetic speed.
SMeared SPectrum(SMSP) jamming has lots of coupling in time and frequency domain with Linear Frequency Modulated(LFM) radar signals, which has good jamming performance. This paper proposes a signal processing method for countering SMSP jamming in information domain. According to the formulation and characteristics of SMSP signal, the jamming dictionary is changed automatically, the frequency modulation rate of LFM and SMSP signal is matcheal at the same time, the compressed sampling model is consructed and reconstruction of signal is carried out based on convex optimization. Finally, the recognition of jamming signal and extraction of radar signal are achieved. Pei type fractional Fourier decomposition method is used in construction of redundant dictionary. Modulation and demodulation between time and frequency domain are avoided in this method, which leads to improvement in fewer iteration times and higher arithmetic speed.
引文
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[16]卢云龙,李明,曹润清,等.联合时频分布和压缩感知对抗频谱弥散干扰[J].电子与信息学报,2016,38(12):3275-3281.doi:10.11999/JEIT160919.LU Yunlong,LI Ming,CAO Runqing,et al.Jointing timefrequency distribution and compressed sensing for countering smeared spectrum jamming[J].Journal of Electronics&Information Technology,2016,38(12):3275-3281.doi:10.11999/JEIT160919.
[17]STARCK J,ELAD M,and DONOHO D.Redundant multiscale transforms and their application for morphological component separation[J].Advances in Imaging&Electron Physics,2004,132(4):287-348.doi:10.1016/S1076-5670(04)32006-9.
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[19]BOBIN J,STARCK J,FADILI J,et al.Morphological component analysis:an adaptive thresholding strategy[J].IEEE Transactions on Image Processing,2007,16(11):2675-2681.doi:10.1109/TIP.2007.907073.
[20]李映,张艳宁,许星.基于信号稀疏表示的形态成分分析:进展和展望[J].电子学报,2009,37(1):146-152.doi:10.3321/j.issn:0372-2112.2009.01.026.LI Ying,ZHANG Yanning,and XU Xing.Advances and perspective on morphological component analysis based on sparse representation[J].Acta Electronica Sinica,2009,37(1):146-152.doi:10.3321/j.issn:0372-2112.2009.01.026.
[21]付蓉,李洁,高新波.基于形态学成分分析的静态极光图像分类算法[J].光子学报,2010,39(6):1034-1039.doi:10.3788/gzxb20103906.1034.FU Rong,LI Jie,and GAO Xinbo.Static aurora images classification based on morphological component analysis[J].Acta Photonica Sinica,2010,39(6):1034-1039.doi:10.3788/gzxb20103906.1034.
[22]陶然,邓兵,王越.分数阶傅里叶变换及其应用[M].北京:清华大学出版社,2009:150-152.TAO Ran,DENG Bing,and WANG Yue.Fractional Fourier Transform and Its Applications[M].Beijing:Tsinghua University Press,2009:150-152.
[2]那洪祥.基于DRFM的高分辨雷达扩展目标回波仿真技术[J].海军航空工程学院学报,2017,32(4):347-351.doi:10.7682/j.issn.1673-1522.2017.04.002.NA Hongxiang.Extended target echo simulation of highresolution radar based on DRFM[J].Journal of Naval Aeronautical and Astronautical University,2017,32(4):347-351.doi:10.7682/j.issn.1673-1522.2017.04.002.
[3]黄思源,刘东升.基于DRFM的移频旁瓣干扰技术研究[J].现代防御技术,2017,45(6):25-32.doi:10.3969/j.issn.1009-086x.2017.06.005.HUANG Siyuan and LIU Dongsheng.Technology of frequency shift sidelobe jamming based on DRFM[J].Modern Defence Technology,2017,45(6):25-32.doi:10.3969/j.issn.1009-086x.2017.06.005.
[4]唐斌,赵源,蔡天一,等.雷达抗有源干扰技术现状与展望[J].数据采集与处理,2016,31(4):623-639.doi:10.16337/j.1004-9037.2016.04.001.TANG Bin,ZHAO Yuan,CAI Tianyi,et al.Advances and perspectives in radar ECCM techniques of active jamming[J].Journal of Data Acquisition and Processing,2016,31(4):623-639.doi:10.16337/j.1004-9037.2016.04.001.
[5]刘振,隋金坪,魏玺章,等.雷达有源干扰识别技术研究现状与发展趋势[J].信号处理,2017,33(12):1593-1601.doi:10.16798/j.issn.1003-0530.2017.12.010.LIU Zhen,SUI Jinping,WEI Xizhang,et al.The development and prospect of radar active jamming recognition[J].Journal of Signal Processing,2017,33(12):1593-1601.doi:10.16798/j.issn.1003-0530.2017.12.010.
[6]孙闽红,唐斌.距离-速度同步拖引欺骗干扰的频谱特征分析[J].系统工程与电子技术,2009,31(1):83-85.doi:10.3321/j.issn:1001-506X.2009.01.021.SUN Minhong and TANG Bin.Analysis of the frequency spectrum of a simultaneous range-gate-pull-off and velocity gate-pull-off jamming signal[J].Systems Engineering and Electronics,2009,31(1):83-85.doi:10.3321/j.issn:1001-506X.2009.01.021.
[7]GRECO M,GINI F,and FARINA A.Combined effect of phase and RGPO delay quantization on jamming signal spectrum[C].2005 IEEE International Radar Conference,Arlington,USA,2005:37-42.
[8]刘兴华,罗景青,王文涛.相位量化DRFM欺骗干扰的自适应检测[J].数据采集与处理,2015,30(6):1302-1309.doi:10.16337/j.1004-9037.2015.06.020.LIU Xinghua,LUO Jingqing,and WANG Wentao.Adaptive detection of phase quantized DRFM deception jamming[J].Journal of Data Acquisition and Processing,2015,30(6):1302-1309.doi:10.16337/j.1004-9037.2015.06.020.
[9]田晓.雷达有源欺骗干扰综合感知方法研究[D].[博士论文],电子科技大学,2013.TIAN Xiao.Research on the integrated perception method of radar active deception[D].[Ph.D.dissertation],University of Electronic Science and Technology of China,2013.
[10]杨少奇,田波,李欣,等.基于时频图像特征提取的LFM雷达有源欺骗干扰识别[J].空军工程大学学报·自然科学版,2016,17(1):56-59.doi:10.3969/j.issn.1009-3516.2016.01.011.YANG Shaoqi,TIAN Bo,LI Xin,et al.A recognition method of LFM radar active deception jamming based on SPWVD figure[J].Journal of Air Force Engineering University,2016,17(1):56-59.doi:10.3969/j.issn.1009-3516.2016.01.011.
[11]周利华.雷达干扰信号分析技术研究[D].[博士论文],西安电子科技大学,2014.ZHOU Lihua.A study on multi-scale feature-level identification of active deception jamming[D].[Ph.D.dissertation],Xidian University,2014.
[12]NOURI M,MIVEHCHY M,and AGHDAM S.Adaptive time-frequency kernel local fisher discriminant analysis to distinguish range deception jamming[C].International Conference on Computing,Communication and Networking Technologies,Denton,USA,2016:1-5.
[13]ZHANG Gexiang and LI Xu.A new recognition system for radar emitter signals[J].Kybernetes,2013,41(9):1351-1360.doi:10.1108/03684921211275405.
[14]SWAMI A and SADLER B.Hierarchical digital modulation classification using cumulants[J].IEEE Transactions on Communications,2000,48(3):416-429.doi:10.1109/26.837045.
[15]LI Jianxun,QI Shen,and HAI Yan.Signal feature analysis and experimental verification of radar deception jamming[C].IEEE CIE International Conference on Radar,Chengdu,China,2012:230-233.
[16]卢云龙,李明,曹润清,等.联合时频分布和压缩感知对抗频谱弥散干扰[J].电子与信息学报,2016,38(12):3275-3281.doi:10.11999/JEIT160919.LU Yunlong,LI Ming,CAO Runqing,et al.Jointing timefrequency distribution and compressed sensing for countering smeared spectrum jamming[J].Journal of Electronics&Information Technology,2016,38(12):3275-3281.doi:10.11999/JEIT160919.
[17]STARCK J,ELAD M,and DONOHO D.Redundant multiscale transforms and their application for morphological component separation[J].Advances in Imaging&Electron Physics,2004,132(4):287-348.doi:10.1016/S1076-5670(04)32006-9.
[18]STARCK J,ELAD M,and DONOHO D.Image decomposition via the combination of sparse representations and a variational approach[J].IEEE Transactions on Image Processing,2005,14(10):1570-1582.doi:10.1109/TIP.2005.852206.
[19]BOBIN J,STARCK J,FADILI J,et al.Morphological component analysis:an adaptive thresholding strategy[J].IEEE Transactions on Image Processing,2007,16(11):2675-2681.doi:10.1109/TIP.2007.907073.
[20]李映,张艳宁,许星.基于信号稀疏表示的形态成分分析:进展和展望[J].电子学报,2009,37(1):146-152.doi:10.3321/j.issn:0372-2112.2009.01.026.LI Ying,ZHANG Yanning,and XU Xing.Advances and perspective on morphological component analysis based on sparse representation[J].Acta Electronica Sinica,2009,37(1):146-152.doi:10.3321/j.issn:0372-2112.2009.01.026.
[21]付蓉,李洁,高新波.基于形态学成分分析的静态极光图像分类算法[J].光子学报,2010,39(6):1034-1039.doi:10.3788/gzxb20103906.1034.FU Rong,LI Jie,and GAO Xinbo.Static aurora images classification based on morphological component analysis[J].Acta Photonica Sinica,2010,39(6):1034-1039.doi:10.3788/gzxb20103906.1034.
[22]陶然,邓兵,王越.分数阶傅里叶变换及其应用[M].北京:清华大学出版社,2009:150-152.TAO Ran,DENG Bing,and WANG Yue.Fractional Fourier Transform and Its Applications[M].Beijing:Tsinghua University Press,2009:150-152.