Study on the Performance of Chaotic Oscillator in Weak Signal Detection

2012 ◽  
Vol 263-266 ◽  
pp. 516-520
Author(s):  
Yan Mang Su ◽  
Zhen Bin Gao ◽  
Xiao Zhe Liu ◽  
Na Zheng
Keyword(s):  
Initial Phase ◽  
Signal To Noise Ratio ◽  
Sampling Frequency ◽  
Signal Frequency ◽  
Chaotic Oscillator ◽  
Reference Frequency ◽  
Weak Signal Detection ◽  
Accuracy Rate ◽  
Frequency Detection ◽  
Output Variance

For the frequency detection by using chaotic oscillator, in this paper, the results which are under the influence of the sampling frequency on the basis of theory that the output variance of the system will reach a maximum when the reference frequency equals to the signal frequency are analyzed. Experiments have indicated that the accuracy rate of the results will be improved and the signal to noise ratio (SNR) threshold will be reduced by increasing the sampling frequency to a certain degree. Besides, we have a further research on detecting the frequency of a signal with an initial phase based on the theory mentioned above, simulation experimental results have verified the output variance still has a drastic change when the reference frequency is equal to the signal frequency.

A New Method of Chaotic Detection for Weak Sinusoidal Signal Frequency

2013 ◽  
Vol 756-759 ◽  
pp. 265-270
Author(s):  
Fang Ling Zeng ◽  
Yan Yan Hu ◽  
Xiao Juan Geng ◽  
Shi Gui Zhang
Keyword(s):  
Duffing Oscillator ◽  
Single Frequency ◽  
Signal Frequency ◽  
Specific Reference ◽  
Detection Accuracy ◽  
Reference Frequency ◽  
Complex Frequency ◽  
Frequency Signal ◽  
Frequency Detection ◽  
Intermittent Chaos

This paper describes the intermittent chaos detection principle, combined with differential form the double Duffing oscillator difference system to the weak signal frequency detection, gives the detailed steps of the method and flow chart. Use the feature that Duffing oscillators with specific reference frequency are insensible to other frequency signals interference, only sensitive to a small part of the nearby specific frequency signal, it comes to a conclusion that small amplitude periodic motion and intermittent chaos motion may appear at the same time in the detection system, which can be used to detect complex frequency signals. At last, takes the single frequency signal and the complex frequency signal detection for simulation, the results show that, compared with traditional Duffing oscillator array method, this method not only reduces the array number, and improved frequency detection bandwidth without affecting the detection accuracy, reduces the calculation amount, so its much better than the traditional method for frequency detection.

Ultrasonic Phased Array Industrial Imaging with Sub-Nyquist Sampling Rate

2013 ◽  
Vol 347-350 ◽  
pp. 327-331
Author(s):  
Guang Zhi Dai ◽  
Guo Qiang Han ◽  
Xian Yue Ouyang
Keyword(s):  
High Speed ◽  
Phased Array ◽  
Signal To Noise Ratio ◽  
Signal Reconstruction ◽  
Sampling Rate ◽  
Sampling Frequency ◽  
Frequency Resolution ◽  
Signal Frequency ◽  
Beam Focusing ◽  
Ultrasonic Phased Array

this paper uses a new type of FRI (Finite Rate of Innovation) sampling pattern based Sub-Nyquist sampling model breaked through Shannon theorem that it can get accurate signal reconstruction based on signal information rate, which requires the sampling frequency lower than two times the max signal frequency. We apply the new model in the ultrasonic phased array industrial imaging. In the experiment, ultrasonic phased array realized dynamic focusing and the high speed scan by ultrasonic array transducer of various array time delays to get flexible controllable synthesis beam composed signals that received by 32 phased array elements . The results indicate that in the model it greatly reduces the signal sampling frequency and improves the signal-to-noise ratio, frequency resolution at the same of the beam focusing and steering flexible.

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.

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.

Weak Signal Frequency Detection Method Based on Generalized Duffing Oscillator

2011 ◽  
Vol 28 (4) ◽  
pp. 040502 ◽  
Author(s):  
Si-Hong Shi ◽  
Yong Yuan ◽  
Hui-Qi Wang ◽  
Mao-Kang Luo
Keyword(s):  
Detection Method ◽  
Duffing Oscillator ◽  
Signal Frequency ◽  
Weak Signal ◽  
Frequency Detection

scholarly journals Optimal nonlinear filtering of M-PSK signals against a background of harmonic interference with a random initial phase

2021 ◽  
Vol 9 (6) ◽  
pp. 46-56
Author(s):  
G. V. Kulikov ◽  
Trung Tien Do ◽  
E. V. Samokhina
Keyword(s):  
Initial Phase ◽  
Nonlinear Filtering ◽  
Noise Immunity ◽  
Signal To Noise Ratio ◽  
Radio Channel ◽  
Complete Suppression ◽  
Two Phase ◽  
Probability Of Error ◽  
Useful Signal ◽  
Optimal Nonlinear Filtering

Objectives. The widespread use of radio data transmission systems using signals with multiposition phase shift keying (MPSK) is due to their high noise immunity and the simplicity of constructing the transmitting and receiving parts of the equipment. The conducted studies have shown that the presence of non-fluctuation interference, in particular, harmonic interference, in the radio channel significantly reduces the noise immunity of receiving discrete information. The energy loss in this case, depending on the interference intensity, can range from fractions of dB to 10 db or more. Therefore, interference suppression is an important task for such radio systems. The aim of the work is to synthesize and analyze an algorithm for optimal nonlinear filtering of MPSK signals against a background of harmonic interference with a random initial phase.Methods. The provisions of the theory of optimal nonlinear signal filtering and methods of statistical radio engineering are used.Results. The synthesis and analysis of the algorithm of optimal nonlinear filtering of MPSK signals against the background of harmonic interference with a random initial phase are carried out. The synthesized receiver contains a discrete symbol evaluation unit, two phase-locked frequency circuits of reference generators that form evaluation copies of the signal and interference, and cross-links between them. Analytical expressions are obtained that allow calculating the dependences of the bit error probability on the signal-to-noise ratio and the interference intensity µ. It is established that uncompensated fluctuations of the initial phase of the useful signal have a greater effect on the receiver noise immunity than similar fluctuations of the phase of harmonic interference, especially with low positional signals.Conclusions. Comparison of the obtained results with the results obtained in the case when there are no harmonic interference compensation circuits shows that the use of the obtained phase filtering algorithms allows for almost complete suppression of harmonic interference. Thus, if µ = 0.5 and the probability of error is 10−2, the energy gain at M = 2 is about 2.5 dB, at M = 4 – about 6 dB, at M = 8 and M = 16 – at least 10 dB.

Improving Switched Current Sigma Delta Modulators’ Performances via the Particle Swarm Optimization Technique

2012 ◽  
pp. 154-170
Author(s):  
M. Fakhfakh ◽  
S. Masmoudi ◽  
Y. Cooren ◽  
M. Loulou ◽  
P. Siarry
Keyword(s):  
Signal To Noise Ratio ◽  
Optimization Technique ◽  
Memory Cell ◽  
Sampling Frequency ◽  
Embryonic Cell ◽  
Signal To Noise ◽  
Swarm Optimization ◽  
Sigma Delta ◽  
Switched Current ◽  
Particle Swarm Optimization Technique

This paper presents the optimal design of a switched current sigma delta modulator. The Multi-objective Particle Swarm Optimization technique is adopted to optimize performances of the embryonic cell forming the modulator, that is, a class AB grounded gate switched current memory cell. The embryonic cell was optimized regarding to its main performances such as sampling frequency and signal to noise ratio. The optimized memory cell was used to design the switched current modulator which operates at a 100 MHz sampling frequency and the output signal spectrum presents a 45.75 dB signal to noise ratio.

Improving Switched Current Sigma Delta Modulators' Performances via the Particle Swarm Optimization Technique

2010 ◽  
Vol 1 (2) ◽  
pp. 18-33 ◽  
Author(s):  
M. Fakhfakh ◽  
S. Masmoudi ◽  
Y. Cooren ◽  
M. Loulou ◽  
P. Siarry
Keyword(s):  
Signal To Noise Ratio ◽  
Optimization Technique ◽  
Memory Cell ◽  
Sampling Frequency ◽  
Embryonic Cell ◽  
Signal To Noise ◽  
Swarm Optimization ◽  
Sigma Delta ◽  
Switched Current ◽  
Particle Swarm Optimization Technique

This paper presents the optimal design of a switched current sigma delta modulator. The Multi-objective Particle Swarm Optimization technique is adopted to optimize performances of the embryonic cell forming the modulator, that is, a class AB grounded gate switched current memory cell. The embryonic cell was optimized regarding to its main performances such as sampling frequency and signal to noise ratio. The optimized memory cell was used to design the switched current modulator which operates at a 100 MHz sampling frequency and the output signal spectrum presents a 45.75 dB signal to noise ratio.

High Speed Under-Sampling Frequency Measurements on FPGA

2017 ◽  
Vol 7 (3) ◽  
pp. 1316
Author(s):  
Seyed Ehsan Yasrebi Naeini ◽  
Ali Maroosi
Keyword(s):  
Field Programmable Gate Array ◽  
High Speed ◽  
Sampling Rate ◽  
Sampling Frequency ◽  
Phase Changes ◽  
Frequency Measurements ◽  
Frequency Detection ◽  
Field Programmable ◽  
Under Sampling ◽  
Nyquist Rate

A Sampling rate is less than Nyquist rate in some applications because of hardware limitations. Consequently, extensive researches have been conducted on frequency detection from sub-sampled signals. Previous studies on under-sampling frequency measurements have mostly discussed under-sampling frequency detection in theory and suggested possible methods for fast under-sampling frequencies detection. This study examined few suggested methods on Field Programmable Gate Array (FPGA) for fast under-sampling frequencies measurement. Implementation of the suggested methods on FPGA has issues that make them improper for fast data processing. This study tastes and discusses different methods for frequency detection including Least Squares (LS), Direct State Space (DSS), Goertzel filter, Sliding DFT, Phase changes of Fast Furrier Transform (FFT), peak amplitude of FFT to conclude which one from these methods are suitable for fast under-sampling frequencies detection on FPGA. Moreover, our proposed approach for sub-sampling detection from real waveform has less complextity than previous approaches from complex waveform.

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