基于Poincare截面的微弱信号定量检测与幅值参数提取

doi:10.3969/j.issn.1001-506X.2020.06.02

系统工程与电子技术 ›› 2020, Vol. 42 ›› Issue (6): 1210-1217.doi: 10.3969/j.issn.1001-506X.2020.06.02

基于Poincare截面的微弱信号定量检测与幅值参数提取

凌云飞^1,²(), 陈长兴¹(), 牛德智³(), 陈婷⁴()

1. 空军工程大学基础部, 陕西西安 710043
2. 空军航空大学航空作战勤务学院, 吉林长春 130022;
3. 国防科技大学信息通信学院试验训练基地, 陕西西安 710106;
4. 空军工程大学信息与导航学院, 陕西西安 710077

收稿日期:2019-08-29 出版日期:2020-06-01 发布日期:2020-06-01
作者简介:凌云飞(1992-),男,讲师,博士,主要研究方向为微弱信号检测技术。E-mail:lingyunf0421@hotmail.com|陈长兴(1964-),男,教授,博士,主要研究方向为电子系统综合化工程。E-mail:xachenchangxing@126.com|牛德智(1984-),男,讲师,博士,主要研究方向为微弱信号检测技术。E-mail:niudezhi_001@163.com|陈婷(1992-),女,博士研究生,主要研究方向为信号处理技术。E-mail:chenting@sxasic.com
基金资助:
国家自然科学基金(61701534);陕西省自然科学基础研究计划(2019JQ-715)

Weak signal quantitative detection and amplitude parameters extraction based on Poincare section

Yunfei LING^1,²(), Changxing CHEN¹(), Dezhi NIU³(), Ting CHEN⁴()

1. Department of Basic Sciences, Air Force Engineering University, Xi'an 710043, China
2. Aviation Combat and Service Institute, Air Force Aviation University, Changchun 130022, China
3. Experimental Training Base of Information and Communications College, National University of Defense Technology, Xi'an 710106, China
4. College of Information and Navigation, Air Force Engineering University, Xi'an 710077, China

Received:2019-08-29 Online:2020-06-01 Published:2020-06-01
Supported by:
国家自然科学基金(61701534);陕西省自然科学基础研究计划(2019JQ-715)

摘要/Abstract

摘要：

为解决微弱信号定量检测问题,提出并建立了基于Poincare截面的检测统计量,并以此设计了利用Duffing振子进行微弱信号定量检测及幅值参数提取的有效实现方法。通过分析Duffing振子的Poincare截面特性,发现系统输出关于幅值的分岔特性能够清晰判定系统不同状态,由此对Poincare截面的分布点进行方差统计,构建检测统计量与检测判定区间,实现对微弱信号的定量检测。仿真实验发现，该定量检测方法的噪声鲁棒性优于传统时域特征检测方法,进一步设计了循环检测系统用以提取待测信号幅值参数并实现对未知频率信号的检测，为基于Duffing振子的微弱信号检测提供了定量检测途径与参考。

关键词: 微弱信号, Duffing振子, Poincare截面, 信号检测, 检测统计量

Abstract:

In order to solve the problem of quantitative detection of weak signals, the detection statistics based on the Poincare section is proposed. An effective quantitative detection method based on the Duffing oscillator is designed, and the amplitude parameters can be extracted with this method. By analyzing the Poincare section characteristics of the Duffing oscillator, it is found that different states of the system can be distinguished by the bifurcation characteristics of the system. Then, the variance statistics of the Poincare section distribution points are determined, the detection statistics and detection determination intervals are formulated to realize the quantitative detection. The simulation results show that the noise robustness of the quantitative detection method is better than that of the traditional time-domain feature detection method. Furthermore, a cyclic detection system is designed to extract the amplitude parameters and detect the unknown frequency signals. The results provide a quantitative detection approach and reference for weak signals detection based on the Duffing oscillator.

Key words: weak signal, Duffing oscillator, Poincare section, signal detection, detection statistic

中图分类号:

TN911

凌云飞, 陈长兴, 牛德智, 陈婷. 基于Poincare截面的微弱信号定量检测与幅值参数提取[J]. 系统工程与电子技术, 2020, 42(6): 1210-1217.

Yunfei LING, Changxing CHEN, Dezhi NIU, Ting CHEN. Weak signal quantitative detection and amplitude parameters extraction based on Poincare section[J]. Systems Engineering and Electronics, 2020, 42(6): 1210-1217.

图/表 11

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参考文献 30

1	DU L , ZHAO Y P , LEL Y M , et al. Suppression of chaos in a generalized Duffing oscillator with fractional-order deflection[J]. Nonlinear Dynamics, 2018, 92 (4): 1921- 1933.
2	CARROLL T L . Chaos for low probability of detection communications[J]. Chaos, Solitons and Fractals, 2017, 103, 238- 245. doi: 10.1016/j.chaos.2017.06.011
3	GEORGES K . Wireless chaos-based communication systems: a comprehensive survey[J]. IEEE Access, 2016, 4, 2621- 2648. doi: 10.1109/ACCESS.2016.2572730
4	COSTA R A D , LOIOLA M B , EISENCRAFT M . Correlation and spectral properties of chaotic signals generated by a piecewise-linear map with multiple segments[J]. Signal Processing, 2016, 133, 187- 191.
5	WANG X , KINGNI S T , VOLOS C , et al. A fractional system with five terms: analysis, circuit, chaos control and synchronization[J]. International Journal of Electronics, 2018, 106 (1): 109- 120.
6	ZENG T , CHANG S , FAN H , et al. Design and processing of a novel chaos-based stepped frequency synthesized wideband radar signal[J]. Sensors, 2018, 18 (4): 985- 1006. doi: 10.3390/s18040985
7	LI C , XU X , DING Y , et al. Weak photoacoustic signal detection based on the differential Duffing oscillator[J]. International Journal of Modern Physics B, 2018, 32 (9): 1850103. doi: 10.1142/S0217979218501035
8	QUAN Y , LI Y , HU W , et al. FM sequence optimisation of chaotic-based random stepped frequency signal in through-the-wall radar[J]. IET Signal Processing, 2017, 11 (7): 830- 837. doi: 10.1049/iet-spr.2015.0565
9	VAHEDI H , GHAREHPETIAN G B , KARRARI M . Application of Duffing oscillators for passive islanding detection of inverter-based distributed generation units[J]. IEEE Trans.on Power Delivery, 2012, 27 (4): 1973- 1983. doi: 10.1109/TPWRD.2012.2212251
10	KORNETA W , GOMES I . Noise activated bistable sensor based on chaotic system with output defined by temporal coding and firing rate[J]. Chaos, 2017, 27 (11): 111103. doi: 10.1063/1.5006564
11	NEZHAD S M T , NAZARI M , GHARAVOL E A . A novel DoS and DDoS attacks detection algorithm using ARIMA time series model and chaotic system in computer networks[J]. IEEE Communications Letters, 2016, 20 (4): 700- 703. doi: 10.1109/LCOMM.2016.2517622
12	WANG E , JIA C , TONG G , et al. Fault detection and isolation in GPS receiver autonomous integrity monitoring based on chaos particle swarm optimization-particle filter algorithm[J]. Advances in Space Research, 2018, 61 (5): 1260- 1272. doi: 10.1016/j.asr.2017.12.016
13	BIRX D L, PIPENBERG S J. Chaotic oscillators and complex mapping feed forward networks(CMFFNS) for signal detection in noisy environments[C]//Proc.of the International Joint Conference on Neural Networks, 1992: 881-888.
14	LI G Z , ZHANG B . A novel weak signal detection method via chaotic synchronization using Chua's circuit[J]. IEEE Trans.on Industrial Electronics, 2017, 64 (3): 2255- 2265. doi: 10.1109/TIE.2016.2620103
15	MEENAKSHI M V S , ATHISAYANATHAN S , CHINNATHAMBI V , et al. Analytical estimates of the effect of amplitude modulated signal in nonlinearly damped Duffing-van der Pol oscillator[J]. Chinese Journal of Physics, 2017, 55 (6): 2208- 2217. doi: 10.1016/j.cjph.2017.09.009
16	WANG G , CHEN D , LIN J , et al. The application of chaotic oscillators to weak signal detection[J]. IEEE Trans.on Industrial Electronics, 1999, 46 (2): 440- 444. doi: 10.1109/41.753783
17	ZHAO W , WANG L , FAN J . Theory and method for weak signal detection in engineering practice based on stochastic resonance[J]. International Journal of Modern Physics B, 2017, 31 (28): 1750212. doi: 10.1142/S0217979217502125
18	凌云飞, 陈长兴, 牛德智, 等. 双势阱Duffing-van der Pol振子微弱信号检测统计量构造[J]. 系统工程与电子技术, 2019, 41 (10): 2178- 2183. doi: 10.3969/j.issn.1001-506X.2019.10.04
	LING Y F , CHEN C X , NIU D Z , et al. Construction of weak signal detection statistics with double-well Duffing-van der Pol oscillator[J]. Systems Engineering and Electronics, 2019, 41 (10): 2178- 2183. doi: 10.3969/j.issn.1001-506X.2019.10.04
19	GOKYILDIRIM A , UYAROGLU Y , PEHLIVAN I . A novel chaotic attractor and its weak signal detection application[J]. Optik-International Journal for Light and Electron Optics, 2016, 127 (19): 7889- 7895. doi: 10.1016/j.ijleo.2016.05.150
20	RAHIMKHANI P , MOETI R . Numerical solution of the fractional order Duffing-van der Pol oscillator equation by using Bernoulli wavelets collocation method[J]. International Journal of Applied & Computational Mathematics, 2018, 4 (2): 59.
21	LIU H G , LIU X L , YANG J H , et al. Detecting the weak high-frequency character signal by vibrational resonance in the Duffing oscillator[J]. Nonlinear Dynamics, 2017, 89 (4): 2621- 2628.
22	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, 39 (11): 2414- 2421. doi: 10.3969/j.issn.1001-506X.2017.11.04
	WU Y H , MA Q L . Blind detection method of weak signals with Duffing oscillator[J]. Systems Engineering and Electronics, 2017, 39 (11): 2414- 2421. doi: 10.3969/j.issn.1001-506X.2017.11.04
23	LUO W M , ZHANG Y R . Non-periodic pulse signal detection based on variable scale coupled Duffing oscillators[J]. Electronics Letters, 2018, 54 (5): 280- 281. doi: 10.1049/el.2017.3676
24	牛德智, 陈长兴, 陈婷, 等. 基于短时傅里叶变换的Duffing振子微弱信号检测[J]. 航空学报, 2015, 36 (10): 3418- 3429.
	NIU D Z , CHEN C X , CHEN T , et al. Weak signal detection with Duffing oscillator based on short time Fourier transform[J]. Acta Aeronautica et Astronautica Sinica, 2015, 36 (10): 3418- 3429.
25	HOU J , YAN X X , LI P , et al. Weak wide-band signal detection method based on small-scale periodic state of Duffing oscillator[J]. Chinese Physics B, 2018, 27 (3): 209- 219.
26	苏理云, 孙唤唤, 王杰, 等. 混沌噪声背景下微弱脉冲信号的检测及恢复[J]. 物理学报, 2017, 66 (9): 090503.
	SU L Y , SUN H H , WANG J , et al. Detection and estimation of weak pulse signal in chaotic background noise[J]. Acta Physica Sinica, 2017, 66 (9): 090503.
27	CHANG Y , HAO Y , LI C . Phase dependent and independent frequency identification of weak signals based on Duffing oscillator via particle swarm optimization[J]. Circuits, Systems and Signal Processing, 2014, 33 (1): 223- 239. doi: 10.1007/s00034-013-9629-9
28	曹保锋, 李鹏, 李小强, 等. 基于强耦合Duffing振子的微弱脉冲信号检测与参数估计[J]. 物理学报, 2019, 68 (8): 080501.
	CAO B F , LI P , LI X Q , et al. Detection and parameter estimation of weak pulse signal based on strongly coupled Duffing oscillators[J]. Acta Physica Sinica, 2019, 68 (8): 080501.
29	LING Y F , CHEN C X , NIU D Z , et al. Weak signal detection using double-well Duffing-van der Pol oscillator and formulation of detection statistics[J]. Journal of the Physical Society of Japan, 2019, 88 (4): 044001. doi: 10.7566/JPSJ.88.044001
30	牛德智, 陈长兴, 班斐, 等. Duffing振子微弱信号检测盲区消除及检测统计量构造[J]. 物理学报, 2015, 64 (6): 060503.
	NIU D Z , CHEN C X , BAN F , et al. Blind angle elimination method in weak signal detection with Duffing oscillator and construction of detection statistics[J]. Acta Physica Sinica, 2015, 64 (6): 060503.

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基于Poincare截面的微弱信号定量检测与幅值参数提取

Weak signal quantitative detection and amplitude parameters extraction based on Poincare section

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