Weak Signal Detection Based on the Nonlinear Dynamic Model

2012 ◽  
Vol 157-158 ◽  
pp. 887-891
Author(s):  
Xuan Chao Liu ◽  
Pei Pei Li

In order to obtain new ways of weak signal detection, we analyzed the motion states of nonlinear dynamic model Duffing oscillator in the case of different amplitude of input signals by solving the Duffing equation and expounded the basic principles of weak signal detection based on Duffing oscillator phase-change characteristics, further illustrated the relationship between signal detection accuracy and detection time by the experimental, researched the impact on signal detection coming from Gaussian white noise and also pointed out how to use intermittent chaos state to implement weak signal detection. The results showed that Duffing oscillator can be effectively detect the slight changes of input signal in the strong noises background, so as to achieve the purpose of weak signal detection. Compared with existing methods, it could greatly improve the detection results.

2011 ◽  
Vol 128-129 ◽  
pp. 354-358 ◽  
Author(s):  
Yuan Chang ◽  
Chun Wen Li ◽  
Yi Hao

This paper studies the detection of weak signal detection using a Duffing Oscillator, which is sensitive to periodic signals but insensitive to noises. The system transits from chaotic to great periodic motion when coupled to the weak periodic signal to be detected. To efficiently determine the phase transition, a novel numerical criterion is proposed based on the sharp increase of variance when phase change happens. Simulation results verified the effectiveness of this method.


Kybernetes ◽  
2009 ◽  
Vol 38 (10) ◽  
pp. 1662-1668 ◽  
Author(s):  
Junguo Wang ◽  
Jianzhong Zhou ◽  
Bing Peng

2008 ◽  
Vol 57 (4) ◽  
pp. 2053
Author(s):  
Wang Yong-Sheng ◽  
Jiang Wen-Zhi ◽  
Zhao Jian-Jun ◽  
Fan Hong-Da

2015 ◽  
Vol 64 (6) ◽  
pp. 060503
Author(s):  
Niu De-Zhi ◽  
Chen Chang-Xing ◽  
Ban Fei ◽  
Xu Hao-Xiang ◽  
Li Yong-Bin ◽  
...  

2014 ◽  
Vol 568-570 ◽  
pp. 155-161
Author(s):  
Heng Zhi Lu ◽  
Zhi Hui Lai ◽  
Tai Hu Wu

In this paper, we study the scale-transformation weak signal detection method based on chaotic Duffing oscillator. Based on this, the frequency characteristics of the weak single-frequency signal with arbitrary frequency and initial phase can be extracted. Furthermore, we propose a signal frequency interception preprocessing method for analyzing weak multi-frequency signal. After combing the preprocessing method with the weak signal detection method based on chaotic Duffing oscillator, we further propose a novel detection method for weak multi-frequency signal. Based on this novel method, we can extract the frequency characteristics and initial phase characteristics of the weak multi-frequency signal. In this research, we also study the automatic detection of unknown multi-frequency signal. According to the numerical simulation, the novel method we propose in this paper is helpful to extract the frequency parameters and initial phase information of each signal component of the weak multi-frequency signal.


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