A Novel Method of High Frequency Weak Signal Detection Based on Chaotic Oscillator System and Wavelet Transform System

2011 ◽  
Vol 130-134 ◽  
pp. 2770-2773
Author(s):  
Shuo Shi ◽  
Jin Yan Li ◽  
Xue Mai Gu
Keyword(s):  
Wavelet Transform ◽  
Signal Detection ◽  
High Frequency ◽  
Signal To Noise Ratio ◽  
Chaotic Oscillator ◽  
Weak Signal ◽  
Weak Signal Detection ◽  
Signal To Noise ◽  
Weak Signals ◽  
Novel Method

Based on chaotic oscillator system and wavelet transform system, this paper proposes a novel method on high frequency weak signal detection. Chaotic system is a typical non-linear system which is sensitive to certain signals and immune to noise at the same time. Its properties demonstrate the potential application on weak signal detection. Due to the good localization in both time domain and frequency domain, the wavelet transform method can automatically adjust to different frequency components and increase the Signal-to-Noise Ratio. Starting from the analysis of advantages and disadvantages of two signal detection methods, we put forward a combined method that takes advantage of each method to detect weak signals with high frequency. The simulation results show that the novel method can detect weak signals with frequency in an order of magnitude of 107Hz, and the input Signal-to-Noise Ratio threshold could be-42.5dB.

scholarly journals A Memristor Based Chaotic Oscillator for Weak Signal Detection and Its Circuitry Realization

2021 ◽  
Author(s):  
Kaifeng Dong ◽  
Kun Xu ◽  
Youyou Zhou ◽  
Chao Zuo ◽  
Leiming Wang ◽  
...  
Keyword(s):  
Signal Detection ◽  
Detection System ◽  
Signal To Noise Ratio ◽  
Detection Accuracy ◽  
Chaotic Oscillator ◽  
Weak Signal ◽  
Weak Signal Detection ◽  
Noise Performance ◽  
Detection Range ◽  
Implementation Scheme

Abstract A new type of weak signal detection system that combines the memristor and Van der pol-Duffing chaotic system has been proposed in this paper, and the dynamic characteristics of the system are studied. It is observed that the system can change from a chaotic state to a periodic state under different driving force amplitudes. Moreover, as compared with several classical chaotic oscillators, the numerical simulation results show that the system has stronger anti-noise performance with the detectable signal-to-noise ratio reaches -163dB, and has a wider detection range. Its detection accuracy is up to 1 × 10 −9 . More importantly, this paper provides the circuit implementation scheme of the system, and the weak signal can be detected with our designed circuit. This may offer a possible way for weak signal detection system with good performance in anti-noise performance, detection range and accuracy.

Weak Signal Detection System Based on Lock-in Amplifier Technology

2013 ◽  
Vol 389 ◽  
pp. 489-493
Author(s):  
Yong Lv ◽  
Chun Hui Niu ◽  
Yue Qiang Li ◽  
Qing Shan Chen ◽  
Xiao Ying Li ◽  
...  
Keyword(s):  
Signal Detection ◽  
Detection System ◽  
Signal To Noise Ratio ◽  
Weak Signal ◽  
Weak Signal Detection ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Low Pass ◽  
Phase Sensitive ◽  
Lock In

In order to detect the weak signal deeply buried in the noise, a weak signal detection system based on lock-in amplifier is proposed. The system includes the preamplifier circuit, active low pass filter circuit, AC amplifying circuit and phase sensitive demodulation circuit. Test results show that it can greatly increase the signal-to-noise ratio (SNR) up to 12.7db.

The Comparison between Chaos Algorithm and Music Algorithm Applied in Weak Signal Detection

2013 ◽  
Vol 427-429 ◽  
pp. 1552-1556
Author(s):  
Chen Zhang ◽  
Zhen Bin Gao ◽  
Jing Chun Li ◽  
Biao Huang
Keyword(s):  
Signal Detection ◽  
Array Signal Processing ◽  
Signal To Noise Ratio ◽  
Weak Signal ◽  
Weak Signal Detection ◽  
Music Algorithm ◽  
Verilog Hdl ◽  
Simulation Experiments ◽  
Chaos Algorithm ◽  
Core Part

Chaos algorithm is essential in weak signal detection because of its sensibility to weak signals and immunity to noise. This paper applies subspace algorithm which originates from array signal processing to weak signal detection field because of its lower signal to noise ratio. Firstly, the article introduces the principles of two algorithms, then analyses simulation experiments results of real signal data. After that, a conclusion for two algorithms comparison by estimation of computation cost, complexity of implementation and hardware resources occupied is drawn. At the end, the writer designs a duffing chaos module which is the core part of chaotic detection with verilog-hdl.

A Method for Weak Multi-Frequency Signal Feature Extraction Based on Chaotic Duffing Oscillator

2014 ◽  
Vol 568-570 ◽  
pp. 155-161
Author(s):  
Heng Zhi Lu ◽  
Zhi Hui Lai ◽  
Tai Hu Wu
Keyword(s):  
Signal Detection ◽  
Initial Phase ◽  
Detection Method ◽  
Duffing Oscillator ◽  
Frequency Characteristics ◽  
Weak Signal ◽  
Weak Signal Detection ◽  
Frequency Signal ◽  
Preprocessing Method ◽  
Novel Method

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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