A Suppression Algorithm of Blanket-distance Deception Compound Jamming based on Joint Signal-data Processing

Guohong WANG; Jie BAI; Dianxing SUN; Xiangyu ZHANG

doi:10.11999/JEIT170759

Volume 40 Issue 10

Sep. 2018

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Article Navigation > Journal of Electronics & Information Technology > 2018 > 40(10): 2430-2437

Guohong WANG, Jie BAI, Dianxing SUN, Xiangyu ZHANG. A Suppression Algorithm of Blanket-distance Deception Compound Jamming based on Joint Signal-data Processing[J]. Journal of Electronics & Information Technology, 2018, 40(10): 2430-2437. doi: 10.11999/JEIT170759

Citation:

Guohong WANG, Jie BAI, Dianxing SUN, Xiangyu ZHANG. A Suppression Algorithm of Blanket-distance Deception Compound Jamming based on Joint Signal-data Processing[J]. Journal of Electronics & Information Technology, 2018, 40(10): 2430-2437. doi: 10.11999/JEIT170759

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A Suppression Algorithm of Blanket-distance Deception Compound Jamming based on Joint Signal-data Processing

doi: 10.11999/JEIT170759

Institute of Information Fusion, Naval Aeronautics University, Yantai 264001, China

Funds: The National Natural Science Foundation of China (61731023, 61701519, 61501489), Taishan Scholar Climbing Plan

Received Date: 2017-07-26
Rev Recd Date: 2018-06-29

Available Online: 2018-07-30

Publish Date: 2018-10-01

Abstract

Abstract

Considering at the problem that the suppression effect of single signal processing or data processing is poor on blanket-deception compound jamming, a suppression algorithm of blanket-distance deception compound jamming based on joint signal-data processing is proposed. Firstly, the Fractional Fourier Transform (FRFT) domain narrowband filtering and LFM signal reconstruction algorithm are used to suppress the suppression of the signal layer and reduce the leakage probability of the real target. Then, the target tracks and the deception tracks are rejected by using the M/N logic method. Finally, according to the different characteristics of the angle variance between the false targets and the true targets, the false targets are eliminated by the ${\chi ^2}$ test and the clustering algorithm. The simulation results verify the good effect of the algorithm proposed in this paper.
- Joint signal-data processing,
- Blanket-distance deception compound jamming,
- Step-by-step suppression,
- FRactional Fourier Transform (FRFT)

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References(18)

References

ROJA R B and UTTARAKUMARI M. Optimization of orthogonal adaptive waveform design in presence of compound Gaussian clutter for MIMO radar[J]. Springerplus, 2015, 4(1): 1–12 doi: 10.1186/s40064-015-1501-x

廖胜男, 韦杉, 文树梁, 等. 基于相位扰动的抗有源加性复合干扰技术[J]. 航天电子对抗, 2012, 28(1): 24–26 doi: 10.3969/j.issn.1673-2421.2012.01.009

LIAO Shengnan, WEI Shan, WEN Shuliang, et al. An algorithm for restraining active additive compound jamming based on phase-perturbed[J]. Aerospace Electronic Warfare, 2012, 28(1): 24–26 doi: 10.3969/j.issn.1673-2421.2012.01.009

任鹏冲, 叶广强, 刘华伟. 一种有源加性复合干扰的对抗算法研究[J]. 计算机量测与控制, 2016, 24(1): 84–88 doi: 10.16526/j.cnki.11-4762/tp.2016.01.079

REN Pengchong, YE Guangqiang, and LIU Huawei. An algorithm research for restraining active additive compound jamming[J]. Computer Measurement&Control, 2016, 24(1): 84–88 doi: 10.16526/j.cnki.11-4762/tp.2016.01.079

贺照辉, 秦江敏, 马晓岩. 基于PR的雷达抗复合干扰中神经网络特征提取[J]. 空军预警学院学报, 2004, 18(3): 12–15 doi: 10.3969/j.issn.1673-8691.2004.03.005

HE Zhaohui, QIN Jiangmin, and MA Xiaoyan. NN feature extraction with PR radar anti-complex-jamming[J]. Journal of Air Force Radar Academy, 2004, 18(3): 12–15 doi: 10.3969/j.issn.1673-8691.2004.03.005

孙殿星, 王国宏, 贺达超, 等. 雷达组网抗距离-速度欺骗复合干扰技术研究[J]. 现代防御技术, 2016, 44(3): 84–91 doi: 10.3969/j.issn.1009-086x.2016.03.014

SUN Dianxing, WANG Guohong, HE Dachao, et al. Antijamming technique in the presence of range-velocity deception compound jamming based on radar network[J]. Modern Defense Technology, 2016, 44(3): 84–91 doi: 10.3969/j.issn.1009-086x.2016.03.014

户锋刚, 阮怀林. 脉冲多普勒雷达特征分析及干扰识别方法研究[J]. 舰船电子对抗, 2007, 30(3): 30–36 doi: 10.3969/j.issn.1673-9167.2007.03.008

HU Fenggang and RUAN Huailin. Characteristic analysis of pulse Doppler radar and the study of jamming recognition method[J]. Shipboard Electronic Countermeasure, 2007, 30(3): 30–36 doi: 10.3969/j.issn.1673-9167.2007.03.008

龚询, 徐海全, 王国宏, 等. SOJ与RGPO复合干扰下目标跟踪技术[J]. 火力与指挥控制, 2014, 39(8): 22–25 doi: 10.3969/j.issn.1002-0640.2014.08.006

GONG Xun, XU Haiquan, WANG Guohong, et al. Target tracking technique under SOJ and RGPO compound jamming[J]. Fire Control&Command Control, 2014, 39(8): 22–25 doi: 10.3969/j.issn.1002-0640.2014.08.006

田原. 雷达有源复合干扰抑制算法研究与实验数据分析[D]. [硕士论文], 电子科技大学, 2013.

陶然, 邓兵, 王越, 等. 分数阶傅里叶变换及其应用[M]. 北京: 清华大学出版社, 2009: 11–12.

何友, 关键, 彭应宁, 等. 雷达自动检测与恒虚警处理[M]. 北京: 清华大学出版社, 1999: 146–147.

王瑜, 李小波, 周青松, 等. 基于FRFT窄带滤波的LFM信号研究[J]. 火力与指挥控制, 2016, 41(12): 41–43 doi: 10.3969/j.issn.1002-0640.2016.12.009

WANG Yu, LI Xiaobo, ZHOU Qingsong, et al. Study of LFM signal based on FRFT domain narrowband filter[J]. Fire Control&Command Control, 2016, 41(12): 41–43 doi: 10.3969/j.issn.1002-0640.2016.12.009

FAN H L, XU Z, CHENG S Y, et al. The parameters estimation of LFM pulse signal based on FrFT[C]. The 2016 International Conference on Mechanical Engineering and Control System, Wuhan, China, 2017: 249–257.

SONG J and LIU Y. Parameter estimation of LFM signal by direct and spline interpolation based on FrFT[J]. Lecture Notes in Electrical Engineering, 2013, 210: 41–48 doi: 10.1007/978-3-642-34528-9_5

何友, 修建娟, 张晶炜, 等. 雷达数据处理及应用[M]. 北京: 电子工业出版社, 2010: 35–37

饶彬.对抗条件下弹道目标的雷达跟踪技术研究[D]. [博士论文], 国防科学技术大学, 2011

周文辉, 李琳, 陈国海. 一种有效的RGPO干扰识别算法及性能分析[J]. 电子学报, 2007, 35(6): 1165–1169 doi: 10.3321/j.issn:0372-2112.2007.06.031

ZHOU Wenhui, LI Lin, and CHEN Guohai. An effective algorithm for discriminating RGPO with performance analysis[J].Acta Electronic Sinica, 2007, 35(6): 1165–1169 doi: 10.3321/j.issn:0372-2112.2007.06.031

ABAVISANI M and PATEL V M. Multimodal sparse and low-rank subspace clustering[J]. Information Fusion, 2018, 39: 168–177 doi: 10.1016/j.inffus.2017.05.002

ARIAS-CASTRO E and PU X. A simple approach to sparse clustering[J]. Computational Statistics&Data Analysis, 2017, 105(6): 217–228 doi: 10.1016/j.csda.2016.08.003

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