基于Lorenz混沌同步系统的未知频率微弱信号检测
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摘要
针对现有混沌类检测方法存在的不足,提出一种基于混沌同步系统测量强噪声背景下微弱信号频率值的新方法。该方法利用Lorenz混沌系统自身的初值敏感性、噪声免疫性和混沌系统的可同步性,采用驱动-响应法构建同步检测系统对微弱信号进行降噪处理,再结合多信号分类算法处理所得到的同步误差信号,最终实现微弱信号的频率测量。该方法有效解决了单Duffing振子参数设定复杂、运行状态转换时间长和状态判定困难的问题,也无需采用复杂的混沌系统阵列结构求解待测信号的频率值。仿真和实验结果表明新方法能够准确检测出微弱信号的频率,进一步完善了现有混沌类检测方法,为其应用于实际工程提供了新的思路。
Aiming at shortcomings of existing chaotic detection methods, a new method based on chaotic synchronization system was proposed to measure frequency values of weak signals under strong noise background. With the proposed method, characteristics of Lorenz chaotic system, such as, sensitivity to initial values, immunity of noise and synchronism were used, and the drive-response method was adopted to construct a synchronization detection system to de-noise weak signals. Using the multi-signal classification(MUSIC) algorithm, the synchronization error signal was processed to realize frequency measurement of weak signals. It was shown that this method can effectively solve problems of single Duffing oscillator's complex parameter setting, long operation state conversion time and difficult state determination; it does not need complex chaotic system array structure to solve frequency values of weak signals to be measured. The simulation and test results showed that the new method can correctly detect frequency values of weak signals, and further improve the existing chaotic detection methods. The results provided a new idea for application of chaotic synchronization systems in practical engineering.
Aiming at shortcomings of existing chaotic detection methods, a new method based on chaotic synchronization system was proposed to measure frequency values of weak signals under strong noise background. With the proposed method, characteristics of Lorenz chaotic system, such as, sensitivity to initial values, immunity of noise and synchronism were used, and the drive-response method was adopted to construct a synchronization detection system to de-noise weak signals. Using the multi-signal classification(MUSIC) algorithm, the synchronization error signal was processed to realize frequency measurement of weak signals. It was shown that this method can effectively solve problems of single Duffing oscillator's complex parameter setting, long operation state conversion time and difficult state determination; it does not need complex chaotic system array structure to solve frequency values of weak signals to be measured. The simulation and test results showed that the new method can correctly detect frequency values of weak signals, and further improve the existing chaotic detection methods. The results provided a new idea for application of chaotic synchronization systems in practical engineering.
引文
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[15] 李国正,张波.基于Duffing振子检测频率未知微弱信号的新方法[J].仪器仪表学报,2017,38(1):181-189. LI Guozheng,ZHANG Bo.A novel method for detecting weak signal with unknown frequency based on Duffing oscillator[J]. Chinese Journal of Scientific Instrument,2017, 38(1):181-189.
[16] LI Guozheng,ZHANG Bo.A novel weak signal detection method via chaotic synchronization using Chua’s circuit[J].Ieee Transactions on Industrial Electronics,2017, 64(3): 2255-2265.
[17] 孙自强,陈长征,谷艳玲, 等.基于混沌和取样积分技术的大型风电增速箱早期故障诊断[J].振动与冲击,2013,32(9):113-117. SUN Ziqiang,CHEN Changzheng,GU Yanling,et al. Incipient fault diagnosis of large scale wind turbine gearbox based on chaos theory and sampling integral technology[J]. Journal of Vibration and Shock, 2013,32(9):113-117.
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[20] SCHMIDT R O. Multiple emitter location and signal parameter estimation[J].IEEE Transactions on Antennas Propag,1986,34(3): 276-280.
[2] 温宇立,武静,林荣, 等.基于相轨迹的多裂纹管道超声导波检测研究[J].振动与冲击,2017,36(23):114-122. WEN Yuli, WU Jing, LIN Rong, et al. Multi-crack detection in pipes using ultrasonic guided wave based on phase trajectories[J]. Journal of Vibration and Shock, 2017,36(23): 114-122.
[3] 林凌,吴红杰,李刚,等.调制法提高体表内部虚拟超谱图信号检测信噪比[J].光谱学与光谱分析,2012(6):1601-1605. LIN Ling,WU Hongjie,LI Gang,et al.A modulation method to improve the signal-to-noise ratio of internal virtual hyperspectrum of body surface[J]. Spectroscopy and Spectral Analysis,2012(6): 1601 -1605.
[4] 王硕,王辅忠,尚金红, 等.基于随机共振理论对2FSK信号输出误码率的研究[J].振动与冲击,2017,36(19):8-12. WANG Shuo, WANG Fuzhong,SHANG Jinhong, et al. 2FSK signal output error-rate influenced by a nonlinear stochastic resonance system[J]. Journal of Vibration and Shock, 2017, 36(19):8-12.
[5] 徐玉秀,赵晓菲,熊一奇.基于传递路径的多级齿轮箱齿轮裂纹故障识别[J].仪器仪表学报,2016,35(5):1018-1024. XU Yuxiou, ZHAO Xiaofei, XIONG Yiqi.Gear crack fault identification for multi-stage gearbox based on signal propagation path[J]. Journal of Vibration and Shock,2016,35(5): 1018-1024.
[6] WANG Guanyu, CHEN Dajun, LIN Jianya, et al. The application of chaotic oscillators to weak signal detection[J]. IEEE Transactions on Industrial Electronics, 1999, 46(2): 440-444.
[7] 王永生,杜文超,安昕, 等.驱动输入白噪声对Duffing振子运动影响分析[J].振动与冲击,2007,26(3):131-134. WANG Yongsheng, DU Wenchao, AN Xin, et al. Analysis of drive input white noise effect on movement of a Duffing oscillator[J]. Journal of Vibration and Shock, 2007,26(3):131-134.
[8] 吴彦华,马庆力.Duffing振子微弱信号盲检测方法[J].系统工程与电子技术,2017(11):2414-2421. WU Yanhua,MA Qingli.Blind detection method of weak signals with Duffing oscillator[J].Systems Engineering and Electronics, 2017(11):2414-2421.
[9] 孙文军,芮国胜,张驰,等.混沌检测系统对噪声的免疫性分析及稳健建模[J].电子科技大学学报,2017(3):492-497. SUN Wenjun,RUI Guosheng,ZHANG Chi,et al. Analysis on noise immunity of chaotic detection system and robustness modeling approach[J].Journal of University of Electronic Science and Technology of China,2017(3):492-497.
[10] RASHTCHI V,NOURAZAR M.Detecting the stateof the duffing oscillator by phase space trajectory autocorrelation[J]. International Journal of Bifurcation and Chaos,2013, 23(4): 1350065.
[11] AWREJCEWICZ J, PYRYEV Y.Chaos prediction in the duffing-type system with friction using Melnikov’s function[J]. Nonlinear Analysis-Real World Applications, 2006(7):12-24.
[12] ZHAO Zhen,WANG Fuli,JIA Mingxing,et al. Intermittent-chaos-and-cepstrum-analysis-based early fault detection on shuttle valve of hydraulic tube tester[J].IEEE Transactions on Industrial Electronics,2009,56(7):2764-2770.
[13] 张伟伟,马宏伟.利用混沌振子系统识别超声导波信号的仿真研究[J].振动与冲击,2012,31(19):15-20. ZHANG Weiwei, MA Hongwei. Simulations of ultrasonic guided wave identification using a chaotic oscillator[J]. Journal of Vibration and Shock, 2012,31(19):15-20.
[14] 陈志光,李亚安,陈晓.基于Hilbert变换及间歇混沌的水声微弱信号检测方法研究[J].物理学报,2015,64(20):200502. CHEN Zhiguang,LI Ya’an,CHEN Xiao.Underwater acoustic weak signal detection based on Hilbert transform and intermittent chaos[J].Acta Physica Sinica,2015, 64(20): 200502.
[15] 李国正,张波.基于Duffing振子检测频率未知微弱信号的新方法[J].仪器仪表学报,2017,38(1):181-189. LI Guozheng,ZHANG Bo.A novel method for detecting weak signal with unknown frequency based on Duffing oscillator[J]. Chinese Journal of Scientific Instrument,2017, 38(1):181-189.
[16] LI Guozheng,ZHANG Bo.A novel weak signal detection method via chaotic synchronization using Chua’s circuit[J].Ieee Transactions on Industrial Electronics,2017, 64(3): 2255-2265.
[17] 孙自强,陈长征,谷艳玲, 等.基于混沌和取样积分技术的大型风电增速箱早期故障诊断[J].振动与冲击,2013,32(9):113-117. SUN Ziqiang,CHEN Changzheng,GU Yanling,et al. Incipient fault diagnosis of large scale wind turbine gearbox based on chaos theory and sampling integral technology[J]. Journal of Vibration and Shock, 2013,32(9):113-117.
[18] LORENZ E N.Designing chaotic models[J].Journal of the Atmospheric Sciences,2005,62:1574-1587.
[19] SHEVITZ D,PADEN B.Lyapunov stability theory of nonsmooth systems[J].IEEE Transactions on Automatic Control,1994, 39(9): 1910-1914.
[20] SCHMIDT R O. Multiple emitter location and signal parameter estimation[J].IEEE Transactions on Antennas Propag,1986,34(3): 276-280.