scholarly journals WEAK SIGNAL DETECTION BASED ON MULTIPLE AUTO-CORRELATION TECHNIQUES

2021 ◽  
Vol 25 (Special) ◽  
pp. 1-56-1-62
Author(s):  
Sarah S. Mohammed ◽  
◽  
Maher K. Mahmood ◽  
Keyword(s):  
Signal To Noise Ratio ◽  
Probability Of Detection ◽  
Weak Signal ◽  
Weak Signal Detection ◽  
Multiple Correlation ◽  
Signal To Noise ◽  
Probability Of False Alarm ◽  
Auto Correlation ◽  
Simulation Results ◽  
Correlation Techniques

This study presents the performance of the auto-correlation methods for detecting weak signals, where the signal level is much less than the noise level. Double and triple auto-correlation techniques are used to improve the detection performance compared with the single autocorrelation. Simulation results obtained by MATLAB programs show that the multiple correlation techniques outperform the single correlation in terms of probability of detection and probability of false alarm versus signal to noise ratio SNR.

Study on Threshold Detection of Micro-Seismic Signal Based on Constraint Judgment

2011 ◽  
Vol 255-260 ◽  
pp. 2898-2903
Author(s):  
Chang Peng Ji ◽  
Mo Gao ◽  
Jie Yang
Keyword(s):  
Signal To Noise Ratio ◽  
Seismic Signal ◽  
Probability Of Detection ◽  
Identification Accuracy ◽  
Signal To Noise ◽  
Threshold Detection ◽  
Probability Of False Alarm ◽  
Improvement Effect ◽  
The Mathematical Model ◽  
Double Threshold

Double threshold detection based on constraint judgment is proposed for micro-seismic signal detection. The improvement effect on Probability of False Alarm and influence on Probability of Detection are quantitatively analyzed with constraint judgment. The mathematical models of total PFA and PD of double threshold detection based on constraint judgment are built, and the validity of the mathematical model is verified by simulation tests and experiments. The results show that the signal-to-noise ratio under scheduled PFA and PD Call be decreased by introducing constraint judgment to double threshold detection, and improve the identification accuracy of micro-seismic signal.

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 Cooperative Spectrum Sensing Based on Convolutional Neural Networks

2021 ◽  
Vol 11 (10) ◽  
pp. 4440
Author(s):  
Youheng Tan ◽  
Xiaojun Jing
Keyword(s):  
Neural Networks ◽  
Spectrum Sensing ◽  
Convolutional Neural Networks ◽  
Cooperative Spectrum Sensing ◽  
Signal To Noise Ratio ◽  
Majority Voting ◽  
Signal To Noise ◽  
Hidden Terminal ◽  
Simulation Results ◽  
Sensing Performance

Cooperative spectrum sensing (CSS) is an important topic due to its capacity to solve the issue of the hidden terminal. However, the sensing performance of CSS is still poor, especially in low signal-to-noise ratio (SNR) situations. In this paper, convolutional neural networks (CNN) are considered to extract the features of the observed signal and, as a consequence, improve the sensing performance. More specifically, a novel two-dimensional dataset of the received signal is established and three classical CNN (LeNet, AlexNet and VGG-16)-based CSS schemes are trained and analyzed on the proposed dataset. In addition, sensing performance comparisons are made between the proposed CNN-based CSS schemes and the AND, OR, majority voting-based CSS schemes. The simulation results state that the sensing accuracy of the proposed schemes is greatly improved and the network depth helps with this.

An Improved Acquisition Method for High-Order BOC-Modulated Signals Based on Fractal Geometry

2013 ◽  
Vol 846-847 ◽  
pp. 1185-1188 ◽  
Author(s):  
Hua Bing Wu ◽  
Jun Liang Liu ◽  
Yuan Zhang ◽  
Yong Hui Hu
Keyword(s):  
Fractal Geometry ◽  
Output Signal ◽  
Signal To Noise Ratio ◽  
High Order ◽  
Main Peak ◽  
Signal To Noise ◽  
Binary Offset Carrier ◽  
Simulation Results ◽  
Modulated Signals ◽  
Acquisition Method

This paper proposes an improved acquisition method for high-order binary-offset-carrier (BOC) modulated signals based on fractal geometry. We introduced the principle of our acquisition method, and outlined its framework. We increase the main peak to side peaks ratio in the BOC autocorrelation function (ACF), with a simple fractal geometry transform. The proposed scheme is applicable to both generic high-order sine-and cosine-phased BOC-modulated signals. Simulation results show that the proposed method increases output signal to noise ratio (SNR).

Improved Semi-Bit Differential Acquisition Method for Navigation Bit Sign Transition and Code Doppler Compensation in Weak Signal Environment

2020 ◽  
Vol 73 (4) ◽  
pp. 892-911 ◽  
Author(s):  
M. Nezhadshahbodaghi ◽  
M. R. Mosavi ◽  
N. Rahemi
Keyword(s):  
Signal To Noise Ratio ◽  
Integration Time ◽  
Data Sets ◽  
Weak Signal ◽  
Differential Acquisition ◽  
Global Positioning ◽  
Signal Environment ◽  
Correlation Techniques ◽  
Transition Issues ◽  
Acquisition Method

The presence of code Doppler and navigation bit sign transitions means that the acquisition of global positioning system (GPS) signals is difficult in weak signal environments where the output signal-to-noise ratio (SNR) is significantly reduced. Post-correlation techniques are typically utilised to solve these problems. Despite the advantages of these techniques, the post-correlation techniques suffer from problems caused by the code Doppler and the navigation bit sign transitions. We present an improved semi-bit differential acquisition method which can improve the code Doppler and the bit sign transition issues in the post-correlation techniques. In order to overcome the phenomenon of navigation bit sign transitions, the proposed method utilises the properties of the navigation bit. Since each navigation bit takes as long as 20 ms, there would be 10 ms correlations duration integration time between the received signal and the local coarse/acquisition (C/A) code in which the navigation bit sign transitions will not occur. Consequently, this problem can be cancelled by performing 10 ms correlations in even and odd units separately. Compensation of the code Doppler is also accomplished by shifting the code phase of the correlation results. To validate the performance of our suggested method, simulations are performed based on three data sets. The results show that the quantity of required input SNR to detect at least four satellites in the proposed method is − 48·3 dB, compared with − 20 dB and − 9 dB, respectively, in traditional differential and non-coherent methods.

scholarly journals 53 Piscium, an SPB Star with Activity

2002 ◽  
Vol 185 ◽  
pp. 236-237
Author(s):  
J.-M. Le Contel ◽  
P. Mathias ◽  
E. Chapellier ◽  
J.-C. Valtier
Keyword(s):  
High Resolution ◽  
False Alarm ◽  
High Frequency ◽  
Signal To Noise Ratio ◽  
High Signal ◽  
Correlation Technique ◽  
Signal To Noise ◽  
Spectroscopic Observations ◽  
Auto Correlation ◽  
Frequency Variations

The star 53 Psc (HD 3379, B2.5IV) has been observed as variable by several authors (Sareyan et al., 1979) with frequencies around 10 c d–1 and has been classified as a β Cephei star. Conversely, other authors (e.g. Percy, 1971) found it to be constant.New high resolution, high signal-to-noise ratio, Spectroscopic observations have been performed at the Observatoire de Haute-Provence in 1996 over 11 nights. The spectral domain covers around 200 Å and is centered on Hδ. Radial velocities were deduced from an auto-correlation technique with a scatter around 0.4kms−1.No high frequency variations are observed. Three frequencies have been detected with a false alarm detection above the 1 % level. A fourth one may be present but its amplitude is below this 1 % level. Results are displayed in Table 1.

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.

Highly Accurate Frequency Interpolation of Apodized FFT Magnitude-Mode Spectra

1998 ◽  
Vol 52 (1) ◽  
pp. 134-138 ◽  
Author(s):  
Yutaka Goto
Keyword(s):  
Simple Formula ◽  
Previous Investigation ◽  
Signal To Noise Ratio ◽  
Damping Ratio ◽  
Frequency Error ◽  
Signal To Noise ◽  
Window Functions ◽  
Optimal Values ◽  
Simulation Results ◽  
True Frequency

“Generalized” interpolation (called GIα here) of fast Fourier transform (FFT) spectra apodized by a family of sinα ( X) windows has previously been proposed. The GIα gives the highly accurate interpolated frequency by calculating the simple formula of frequency determination with the use of two squared ratios between three magnitudes nearest to the peak maximum on the apodized FFT spectrum. Although the value of window parameter α, limited to integer values, has been used for the GIα, we show in the present paper that the GIα with a real α value also gives an extremely good estimate of the true frequency from the sinα ( X)-apodized spectra. Thus, we intend to apply the GIα with the optimal values of α to FFT spectra apodized by any other window functions that are often used in Fourier spectroscopy. Simulation results show that the GIα is easier and more accurate than the KCe interpolation, which uses a family of interpolating functions [ KCe(ω) = ( aω2 + bω + c)e] proposed by Keefe and Comisarow. Finally, in the presence of noise we examine effects of damping and windowing on the frequency interpolation of FFT spectra. Because damping and windowing reduce the signal-to-noise ratio (SNR), we define anew the relative SNR by the ratio of the SNR of the apodized spectrum of a damped sinusoid to the SNR of the unapodized spectrum of an undamped sinusoid. Numerical calculation shows that the relative SNR varies, owing to damping rather than windowing. In fact, the observed frequency error roughly increases as the damping ratio increases for any window functions, as is expected from our previous investigation that the frequency error based upon the GIα is inversely proportional to the SNR. However, no obvious differences between the various window functions are observed in the presence of noise.

The Design and Simulation of Cycled Amplifying Circuit

2013 ◽  
Vol 462-463 ◽  
pp. 632-635
Author(s):  
Na An ◽  
Cheng Long Gong ◽  
Weng Ming Su
Keyword(s):  
Adaptive Control ◽  
Error Compensation ◽  
Signal To Noise Ratio ◽  
Weak Signal ◽  
Detection Error ◽  
Signal To Noise ◽  
Analog Switch ◽  
Data Acquisition And Processing ◽  
Double Channel ◽  
Device Noise

There are many traditional methods to detect the weak signal(such as, locking -receive, synchronous cumulative and double channel de-noising) When the signal is very weak which easily submerged by the device noise,the error that measured by the above methods is too big. This paper mainly introduces the principle of a adaptive control faint signal cycle amplifier and through the method of error compensation to amplify signal cycled , which improve the signal-to-noise ratio and reduce the detection error. The structure of this system is simple and it cost low. besides,it convenient for use and debug. The circuit can also be applied to data acquisition and processing of weak signal and its significance is very widely .This paper designs a simulation circuit and analyzes sample-hold and analog switch.

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