极低信噪比下对偶序列跳频信号的随机共振检测方法

刘广凯; 全厚德; 孙慧贤; 崔佩璋; 池阔; 姚少林

doi:10.11999/JEIT190157

极低信噪比下对偶序列跳频信号的随机共振检测方法

doi: 10.11999/JEIT190157

1.
陆军工程大学电子与光学工程系石家庄 050003
2.
陆军工程大学装备指挥管理系石家庄 050003
3.
洛阳电子信息装备试验中心洛阳 471000

基金项目: 河北省自然科学基金(F2017506006)

详细信息

作者简介:
刘广凯：男，1990年生，博士生，研究方向为微弱信号检测、通信抗干扰

全厚德：男，1963年生，教授，研究方向为通信抗干扰、指控系统无线效能增强

孙慧贤：男，1980年生，讲师，研究方向为指挥信息系统工程、战术无线通信技术

崔佩璋：男，1974年生，副教授，研究方向为信息与通信系统

池阔：男，1990年生，博士生，研究方向为机械系统状态检测、故障预测与健康管理

姚少林：男，1992年生，助理工程师，研究方向为电子装备测试

通讯作者:
刘广凯　dreamer_gk@163.com

中图分类号: TN918
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出版历程
- 收稿日期: 2019-03-18
- 修回日期: 2019-05-27
- 网络出版日期: 2019-06-03
- 刊出日期: 2019-10-01

Stochastic Resonance Detection Method for the Dual-Sequence Frequency Hopping Signal under Extremely Low Signal-to-Noise Radio

1.
Department of Electronics and Optical Engineering, Army Engineering University, Shijiazhuang 050003, China
2.
Department of Equipment Command and Management, Army Engineering University, Shijiazhuang 050003, China
3.
Luoyang Electronic Equipment Test Center, Luoyang 471000, China

Funds: The Natural Science Foundation of Hebei Province (F2017506006)

摘要

摘要: 针对对偶序列跳频(DSHF)在极低信噪比(SNR)下无法通信的问题，该文充分利用对偶序列跳频信号时、频域物理特征，提出一种随机共振(SR)检测方法，极大扩展该信号的应用场景。首先，通过分析对偶序列跳频的发射、接收信号及超外差解调的中频(IF)信号，构建随机共振系统，采用尺度变换调整中频信号；然后，引入判决时刻，将无定态解的非自治福克普朗克方程(FPE)转化为可解的自治方程，从而推导出含时间参量的概率密度周期定态解；其次，以最大后验概率为准则，得到检测概率、虚警概率和接收机工作特性(ROC)曲线；最后，得出以下结论：(1) 应用匹配随机共振检测对偶序列跳频信号的信噪比最低可达–18 dB；(2)对偶序列跳频与匹配随机共振结合，适用于信噪比在–18～–14 dB的信号检测；(3)应用匹配随机共振检测对偶序列跳频信号在信噪比为–14 dB时，检测性能提升了25.47%。仿真实验验证了理论的正确性。
- 信号检测 /
- 对偶序列跳频 /
- 随机共振 /
- 检测性能
Abstract: Considering the problem that the Dual-Sequence Frequency Hopping (DSFH) can not communicate at extremely low Signal-to-Noise Ratio (SNR), a Stochastic Resonance (SR) detection method is proposed. The SR takes full advantage of the physical characteristics of DSFH signal to improve the detection performance. Firstly, the SR is constructed by analyzing signals of transmission, reception and the Intermediate Frequency (IF). The scale transaction is used to adjust the IF signal to fit the SR. Secondly, the non-autonomous Fokker-Plank Equation (FPE) is transformed into an autonomous equation by introducing the decision time. Therefore, the analytical solution of the probability density function with the parameter of decision time is obtained. Finally, the detection probability, false alarm probability and Receiver Operating Characteristics (ROC) curve are obtained, when the criterion is the Maximum A Posterior probability (MAP). Simulation analysis results show three conclusions: (1) The SNR of DSFH signal can be as low as –18 dB, which uses the matched SR detection. (2) Method for combining DSFH with the matched SR is suitable to detect the signals with SNR of –18 ～–14 dB. (3) In the case of –14 dB SNR, the DFSH signal detection performance increases by 25.47%, when using SR. The proposed method effectiveness is proved with simulation results.
- Signal detection /
- Dual-Sequence Frequency Hopping (DSFH) /
- Stochastic Resonance (SR) /
- Detection performance

HTML全文

图 1 对偶序列跳频发射结构

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图 2 对偶序列跳频接收结构

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图 3 判决区域及判决概率

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图 4 DSFH系统在不同SNR时的射频域时频图

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图 5 对偶序列跳频的中频信号经随机共振系统前后的时频域波形

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图 6 粒子处于不同位置时的概率密度

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图 7 对偶序列跳频信号的随机共振ROC曲线

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图 8 对偶序列跳频信号的随机共振检测性能随SNR变化情况

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图 9 对偶序列跳频信号的随机共振检测概率随先验概率变化情况

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参考文献(18)

FITZEK F H P. The medium is the message[C]. 2006 IEEE International Conference on Communications, Istanbul, Turkey, 2006: 5016–5021.

ZHOU Xin, KYRITSI P, EGGERS P C F, et al. "The medium is the message": Secure communication via waveform coding in MIMO systems[C]. The 65th Vehicular Technology Conference-VTC2007-Spring, Dublin, Ireland, 2007: 491–495.

QUAN Houde, ZHAO Huan, and CUI Peizhang. Anti-jamming frequency hopping system using multiple hopping patterns[J]. Wireless Personal Communications, 2015, 81(3): 1159–1176. doi: 10.1007/s11277-014-2177-1

赵寰, 全厚德, 崔佩璋. 抗跟踪干扰的多序列跳频无线通信系统[J]. 系统工程与电子技术, 2015, 37(3): 671–678. doi: 10.3969/j.issn.1001-506X.2015.03.31

ZHAO Huan, QUAN Houde, and CUI Peizhang. Follower-jamming resistible multi-sequence frequency hopping wireless communication[J]. Systems Engineering and Electronics, 2015, 37(3): 671–678. doi: 10.3969/j.issn.1001-506X.2015.03.31

BENZI R, SUTERA A, and VULPIANI A. The mechanism of stochastic resonance[J]. Journal of Physics A: Mathematical and General, 1981, 14(11): L453–L457. doi: 10.1088/0305-4470/14/11/006

张刚, 宋莹, 张天骐. Levy噪声驱动下指数型单稳系统的随机共振特性分析[J]. 电子与信息学报, 2017, 39(4): 893–900. doi: 10.11999/JEIT160579

ZHANG Gang, SONG Ying, and ZHANG Tianqi. Characteristic analysis of exponential type monostable stochastic resonance under levy noise[J]. Journal of Electronics &Information Technology, 2017, 39(4): 893–900. doi: 10.11999/JEIT160579

王珊, 王辅忠. 基于自适应随机共振理论的太赫兹雷达信号检测方法[J]. 物理学报, 2018, 67(16): 160502. doi: 10.7498/aps.67.20172367

WANG Shan and WANG Fuzhong. Adaptive stochastic resonance system in Terahertz radar signal detection[J]. Acta Physica Sinica, 2018, 67(16): 160502. doi: 10.7498/aps.67.20172367

KRAUSS P, METZNER C, SCHILLING A, et al. Adaptive stochastic resonance for unknown and variable input signals[J]. Scientific Reports, 2017, 7(1): 2450. doi: 10.1038/s41598-017-02644-w

CHEN Hao, VARSHNEY L R, and VARSHNEY P K. Noise-enhanced information systems[J]. Proceedings of the IEEE, 2014, 102(10): 1607–1621. doi: 10.1109/JPROC.2014.2341554

CHEN Hao, VARSHNEY P K, KAY S M, et al. Theory of the stochastic resonance effect in signal detection: Part I—Fixed detectors[J]. IEEE Transactions on Signal Processing, 2007, 55(7): 3172–3184. doi: 10.1109/TSP.2007.893757

CHEN Hao and VARSHNEY P K. Theory of the stochastic resonance effect in signal detection—Part II: Variable detectors[J]. IEEE Transactions on Signal Processing, 2008, 56(10): 5031–5041. doi: 10.1109/TSP.2008.928509

ZHANG Gang, ZHANG Yijun, ZHANG Tianqi, et al. Stochastic resonance in second-order underdamped system with exponential Bistable potential for bearing fault diagnosis[J]. IEEE Access, 2018, 6: 42431–42444. doi: 10.1109/ACCESS.2018.2856620

李海霞, 任勇峰, 杨玉华, 等. 跳频信号的迭代随机共振解调算法[J]. 系统仿真学报, 2018, 30(1): 341–347. doi: 10.16182/j.issn1004731x.joss.201801045

LI Haixia, REN Yongfeng, YANG Yuhua, et al. Iterative stochastic resonance demodulation algorithm of frequency-hopping signal[J]. Journal of System Simulation, 2018, 30(1): 341–347. doi: 10.16182/j.issn1004731x.joss.201801045

WANG Jun, REN Xin, ZHANG Shaowen, et al. Adaptive bistable stochastic resonance aided spectrum sensing[J]. IEEE Transactions on Wireless Communications, 2014, 13(7): 4014–4024. doi: 10.1109/TWC.2014.2317779

胡岗. 随机力与非线性系统[M]. 上海: 上海科技教育出版社, 1994: 222–232.

HU Gang. Stochastic Forces and Nonlinear Systems[M]. Shanghai: Shanghai Scientific and Technological Education Publishing House, 1994: 222–232.

KANG Yanmei. Simulating transient dynamics of the time-dependent time fractional Fokker-Planck systems[J]. Physics Letters A, 2016, 380(39): 3160–3166. doi: 10.1016/j.physleta.2016.07.049

IKOTA R. Approximation to a Fokker-Planck equation for the Brownian motor[J]. Physical Review E, 2018, 97(6): 062111. doi: 10.1103/PhysRevE.97.062111.

胡茑庆. 随机共振微弱特征信号检测理论与方法[M]. 北京: 国防工业出版社, 2012: 85–86.

HU Niaoqing. Theory and Method of Detecting Weak Characteristic Signals of Stochastic Resonance[M]. Beijing: National Defend Industry Press, 2012: 85–86.

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