基于孪生波形设计的频谱弥散干扰抑制方法

doi:10.7527/S1000-6893.2020.24947

电子电气工程与控制

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基于孪生波形设计的频谱弥散干扰抑制方法

刘治东¹, 张群^1,2, 罗迎^1,2, 李瑞¹

1. 空军工程大学信息与导航学院, 西安 710077;
2. 复旦大学波散射与遥感信息国家教育部重点实验室, 上海 200433

收稿日期:2020-11-03 修回日期:2020-12-15 发布日期:2020-12-31
通讯作者: 张群 E-mail:zhangqunnus@gmail.com
基金资助:
国家自然科学基金（61631019，61971434）

A smeared spectrum interference suppression method based on twinwaveform design

LIU Zhidong¹, ZHANG Qun^1,2, LUO Ying^1,2, LI Rui¹

1. Institute of Information and Navigation, Air Force Engineering University, Xi'an 710077, China;
2. Key Laboratory of Wave Scattering and Remote Sensing Information, Fudan University, Shanghai 200433, China

Received:2020-11-03 Revised:2020-12-15 Published:2020-12-31
Supported by:
National Natural Science Foundation of China (61631019, 61971434)

摘要/Abstract

摘要： 频谱弥散（SMSP）干扰是针对线性调频（LFM）脉冲压缩雷达的一种有效干扰手段。基于干扰信号的时频特征，提出了一种基于孪生波形设计的频谱弥散干扰抑制方法。首先，利用初始脉冲发射LFM信号，对受干扰回波进行Gabor变换得到时频分析结果，并估计干扰子脉冲数；其次，基于干扰子脉冲数设计第2个脉冲发射的孪生波形；然后，设计调制信号对干扰后的孪生波形进行时频搬移后重组；最后，通过匹配滤波处理实现干扰抑制。仿真实验表明：所提方法能主动调整设计发射波形相关参数，并有效利用干扰信号的能量，解决在干信比较大时干扰抑制较为困难的问题，避免复杂的信号分离算法。在干信比为25 dB时，经干扰抑制后的信干噪比增益可以达到60 dB以上。

关键词: 干扰抑制, 频谱弥散(SMSP)干扰, 时频分析, 孪生波形, 时频重组

Abstract: The SMeared SPectrum (SMSP) jamming is an effective jamming method against Linear Frequency Modulation (LFM) pulse compression radar. Based on the time-frequency characteristics of the jamming signal, a SMSP jamming suppression method is proposed based on the twin waveform design. First, the LFM signal is transmitted by the initial pulse, and the results of time-frequency analysis are obtained by Gabor transformation of the jamming signal. Then, the number of the interference sub-pulse is estimated. Second, based on the number of the interference sub-pulse, the twin waveform transmitted by the second pulse is designed. Then, modulated signals are designed to carry out time-frequency shift and recombination of the jamming twin waveforms. Finally, interference suppression is realized through matched filtering. Simulation experiments show that the method proposed can actively adjust the relevant parameters of the transmit waveform, and effectively utilize the energy of the interference signal. The method can solve the problem of difficulty in interference suppression when the jamming-to-signal ratio is large, and can avoid the use of complex signal separation algorithm. When the jamming-to-signal ratio is 25 dB, the gain of signal-to-interference plus noise ratio after interference suppression can reach more than 60 dB.

Key words: jamming suppression, SMeared SPectrum (SMSP) jamming, time-frequency analysis, twin waveform, time-frequency restructuring

中图分类号:

V243.2

刘治东, 张群, 罗迎, 李瑞. 基于孪生波形设计的频谱弥散干扰抑制方法[J]. 航空学报, 2022, 43(2): 324947-324947.

LIU Zhidong, ZHANG Qun, LUO Ying, LI Rui. A smeared spectrum interference suppression method based on twinwaveform design[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2022, 43(2): 324947-324947.

参考文献

[1] SPARROW M J, CIKALO J. ECM techniques to counter pulse compression radar:US7081846[P]. 2006-07-25.
[2] 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. TANG B, ZHAO Y, CAI T Y, et al. Advances and perspectives in radar ECCM techniques of active jamming[J]. Journal of Data Acquisition and Processing, 2016, 31(4):623-639(in Chinese).
[3] 杨少奇, 田波. 频谱弥散和切片组合欺骗式干扰的识别算法[J]. 探测与控制学报, 2016, 38(6):62-67. YANG S Q, TIAN B. Identification algorithms of SMSP and C & I[J]. Journal of Detection & Control, 2016, 38(6):62-67(in Chinese).
[4] SOUMEKH M. SAR-ECCM using phase-perturbed LFM chirp signals and DRFM repeat jammer penalization[J]. IEEE Transactions on Aerospace and Electronic Systems, 2006, 42(1):191-205.
[5] 卢刚, 唐斌, 罗双才. LFM雷达中DRFM假目标自适应对消方法[J]. 系统工程与电子技术, 2011, 33(8):1760-1764. LU G, TANG B, LUO S C. Adaptive cancellation of DRFM false targets for LFM radar[J]. Systems Engineering and Electronics, 2011, 33(8):1760-1764(in Chinese).
[6] LI Y P, XIONG Y, BIN T. SMSP jamming identification based on matched signal transform[C]//2011 International Conference on Computational Problem-Solving (ICCP). Piscataway:IEEE Press, 2011:182-185.
[7] 赵杨, 尚朝轩, 韩壮志, 等. 分数阶傅里叶和压缩感知自适应抗频谱弥散干扰[J]. 电子与信息学报, 2019, 41(5):1047-1054. ZHAO Y, SHANG C X, HAN Z Z, et al. Fractional Fourier transform and compressed sensing adaptive countering smeared spectrum jamming[J]. Journal of Electronics & Information Technology, 2019, 41(5):1047-1054(in Chinese).
[8] 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. LU Y L, LI M, CAO R Q, et al. Jointing time-frequency distribution and compressed sensing for countering smeared spectrum jamming[J]. Journal of Electronics & Information Technology, 2016, 38(12):3275-3281(in Chinese).
[9] 张亮, 王国宏, 李思文. 线性正则域抑制频谱弥散干扰方法[J]. 信号处理, 2020, 36(3):328-336. ZHANG L, WANG G H, LI S W. SMSP jamming suppression methods in linear canonical domain[J]. Journal of Signal Processing, 2020, 36(3):328-336(in Chinese).
[10] 李欣, 王春阳, 原慧, 等. 基于干扰重构和峭度最大化的SMSP干扰抑制方法[J]. 北京航空航天大学学报, 2018, 44(6):1176-1184. LI X, WANG C Y, YUAN H, et al. SMSP jamming suppression method based on jamming reconstruction and kurtosis maximum[J]. Journal of Beijing University of Aeronautics and Astronautics, 2018, 44(6):1176-1184(in Chinese).
[11] 原慧, 王春阳, 安磊, 等. 基于信号重构的频谱弥散干扰抑制方法[J]. 系统工程与电子技术, 2017, 39(5):960-967. YUAN H, WANG C Y, AN L, et al. Smeared spectrum jamming suppression method based on signal reconstruction[J]. Systems Engineering and Electronics, 2017, 39(5):960-967(in Chinese).
[12] 张亮, 王国宏, 李思文. 联合时频重排和双正交傅里叶变换对抗频谱弥散干扰[J]. 信号处理, 2020, 36(4):495-501. ZHANG L, WANG G H, LI S W. Jointing time-frequency reassignment and biorthogonal Fourier transform countering smeared spectrum jamming[J]. Journal of Signal Processing, 2020, 36(4):495-501(in Chinese).
[13] 张亮, 王国宏, 张翔宇, 等. 基于多阶次二维分数阶傅里叶变换的频谱弥散干扰抑制算法[J]. 兵工学报, 2020, 41(9):1826-1836. ZHANG L, WANG G H, ZHANG X Y, et al. Smeared spectrum jamming suppression algorithm based on multiple orders 2D-FRFT[J]. Acta Armamentarii, 2020, 41(9):1826-1836(in Chinese).
[14] LI X, WANG C Y, YUAN H, et al. Smeared spectrum jamming suppression based on time unit analysis and polarization cancellation[J]. Cluster Computing, 2019, 22(6):14367-14375.
[15] LI X, WANG C Y, TAN M, et al. Smeared spectrum jamming suppression based on generalized S transform and threshold segmentation[C]//AIP Conference Proceedings. Melville:AIP, 2018,1955(1):040147.
[16] WU C Z, CHEN B X, YANG M L, et al. A study on parameter estimation and suppression for smeared spectrum jamming based on short-time Fourier transform[J]. EURASIP Journal on Wireless Communications and Networking, 2020, 2020:115.
[17] 朱玉鹏, 张月辉, 王宏强, 等. 基于调频率微调的ISAR抗干扰技术研究[J]. 信号处理, 2010, 26(3):417-423. ZHU Y P, ZHANG Y H, WANG H Q, et al. Research on anti-jamming of inverse synthetic aperture radar based on slope-varying LFM signal[J]. Signal Processing, 2010, 26(3):417-423(in Chinese).
[18] 王鑫, 秦琨, 秦轶炜. 基于干扰认知的智能化雷达干扰对抗系统[J]. 电子信息对抗技术, 2018, 33(6):48-52. WANG X, QIN K, QIN Y W. Intelligent anti-jamming system of rader based on jamming recognition[J]. Electronic Information Warfare Technology, 2018, 33(6):48-52(in Chinese).
[19] 祝欢, 孙俊, 杨予昊, 等. 基于环境感知的认知雷达抗干扰技术[J]. 中国电子科学研究院学报, 2016, 11(6):577-581. ZHU H, SUN J, YANG Y H, et al. Interference suppression in cognitive radar based on environment perception[J]. Journal of China Academy of Electronics and Information Technology, 2016, 11(6):577-581(in Chinese).
[20] 唐波. 宽带认知雷达低峰均比波形快速设计算法[J]. 航空学报, 2016, 37(2):688-694. TANG B. Efficient design algorithm of low PAR waveform for wideband cognitive radar[J]. Acta Aeronautica et Astronautica Sinica, 2016, 37(2):688-694(in Chinese).
[21] 崔国龙, 余显祥, 杨婧, 等. 认知雷达波形优化设计方法综述[J]. 雷达学报, 2019, 8(5):537-557. CUI G L, YU X X, YANG J, et al. An overview of waveform optimization methods for cognitive radar[J]. Journal of Radars, 2019, 8(5):537-557(in Chinese).
[22] 叶珍, 白璘, 粘永健. 基于Gabor特征与局部保护降维的高光谱图像分类算法[J]. 光学学报, 2016, 36(10):512-521. YE Z, BAI L, NIAN Y J. Hyperspectral image classification algorithm based on Gabor feature and locality-preserving dimensionality reduction[J]. Acta Optica Sinica, 2016, 36(10):512-521(in Chinese).
[23] 夏赛强, 向虎, 陈文峰, 等. 基于CEMD的旋翼微动目标杂波抑制方法[J]. 航空学报, 2018, 39(9):322091. XIA S Q, XIANG H, CHEN W F, et al. Clutter suppression method for rotor micro-motion target based on CEMD[J]. Acta Aeronautica et Astronautica Sinica, 2018, 39(9):322091(in Chinese).
[24] JIA S, ZHU Z X, SHEN L L, et al. A two-stage feature selection framework for hyperspectral image classification using few labeled samples[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2014, 7(4):1023-1035.
[25] DUNN D F, HIGGINS W E. Optimal Gabor-filter design for texture segmentation[C]//1993 IEEE International Conference on Acoustics, Speech, and Signal Processing. Piscataway:IEEE Press, 1993:4789782.
[26] 闫琰, 李明, 卢云龙. 基于多特征联合处理的灵巧噪声干扰识别[J]. 雷达科学与技术, 2013, 11(5):455-461. YAN Y, LI M, LU Y L. Multi-feature-based identification of smart noise jamming[J]. Radar Science and Technology, 2013, 11(5):455-461(in Chinese).

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基于孪生波形设计的频谱弥散干扰抑制方法

A smeared spectrum interference suppression method based on twinwaveform design

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