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.

scholarly journals On the application of frequency tagging

2020 ◽  
Author(s):  
Zoltan Derzsi
Keyword(s):  
Phase Noise ◽  
Detection Probability ◽  
Signal To Noise Ratio ◽  
Lower Probability ◽  
Weak Signal ◽  
Signal To Noise ◽  
Noise Component ◽  
Spectral Evaluation ◽  
Human Electrophysiology ◽  
Additional Phase

To detect a weak signal in human electrophysiology that is a response of a periodic external stimulus, spectral evaluation is mostly used. The recorded signal’s amplitude and phase noise components of the signal are statistically independent from each other, but both of them are decreasing the signal-to-noise ratio, which results in a lower probability of successful signal detection. Provided that the phase information of the stimuli is preserved, we found that a way to reject an additional phase noise component, which improves the detection probability considerably, by analysing the signal’s phase coherency instead of its spectrum.

Adaptation of Telegraph Diffusion Equation for Noise Reduction on Images

2017 ◽  
Vol 17 (02) ◽  
pp. 1750010 ◽  
Author(s):  
Pandry Koffi Ghislain ◽  
Georges Lausanne Loum ◽  
Ouattara Nouho
Keyword(s):  
Diffusion Equation ◽  
Noise Reduction ◽  
Local Structure ◽  
Signal To Noise Ratio ◽  
Input Image ◽  
Weak Signal ◽  
Signal To Noise ◽  
Reduction Processes ◽  
Fine Structures

The Telegraph Diffusion Equation (TDE) used in some noise reduction processes in an image includes two main parameters: the damping coefficient and the relaxation time. Classically, the first is determined globally for a given input image, while the second one is set constant. In this paper, we propose to determine the values of these parameters according to the information and the image local structure. We then get an adaptive diffusion equation that permits to better control the degree of smoothness and preserve fine structures and image contours avoiding speckles phenomena and staircase. The acquired results show that the proposed method improves the quality of images that have a weak signal-to-noise ratio, comparatively to the methods based on the TDE whose parameters are not adaptive.

scholarly journals Weak Signal Extraction from Lunar Penetrating Radar Channel 1 Data Based on Local Correlation

Electronics ◽  
2019 ◽  
Vol 8 (5) ◽  
pp. 573 ◽  
Author(s):  
Zhuo Jia ◽  
Sixin Liu ◽  
Ling Zhang ◽  
Bin Hu ◽  
Jianmin Zhang
Keyword(s):  
Signal To Noise Ratio ◽  
Lunar Regolith ◽  
Signal Extraction ◽  
Weak Signal ◽  
Human Beings ◽  
Subsurface Structure ◽  
Local Correlation ◽  
Signal To Noise ◽  
Near Surface ◽  
Noise Ratio

Knowledge of the subsurface structure not only provides useful information on lunar geology, but it also can quantify the potential lunar resources for human beings. The dual-frequency lunar penetrating radar (LPR) aboard the Yutu rover offers a Special opportunity to understand the subsurface structure to a depth of several hundreds of meters using a low-frequency channel (channel 1), as well as layer near-surface stratigraphic structure of the regolith using high-frequency observations (channel 2). The channel 1 data of the LPR has a very low signal-to-noise ratio. However, the extraction of weak signals from the data represents a problem worth exploring. In this article, we propose a weak signal extraction method in view of local correlation to analyze the LPR CH-1 data, to facilitate a study of the lunar regolith structure. First, we build a pre-processing workflow to increase the signal-to-noise ratio (SNR). Second, we apply the K-L transform to separate the horizontal signal and then use the seislet transform (ST) to reserve the continuous signal. Then, the local correlation map is calculated using the two denoising results and a time–space dependent weighting operator is constructed to suppress the noise residuals. The weak signal after noise suppression may provide a new reference for subsequent data interpretation. Finally, in combination with the regional geology and previous research, we provide some speculative interpretations of the LPR CH-1 data.

scholarly journals Обнаружение хаотических радиоимпульсов с помощью ансамбля детекторов огибающих

2021 ◽  
Vol 47 (1) ◽  
pp. 27
Author(s):  
Ю.В. Андреев
Keyword(s):  
Analytical Solution ◽  
Error Probability ◽  
Signal To Noise Ratio ◽  
Radio Pulse ◽  
Detection Error ◽  
Signal To Noise ◽  
Pulse Detection ◽  
Noise Ratio

Detection of ultrawideband chaotic radio pulses with ensemble of noncoherent receivers based on envelope detectors is investigated. Analytical solution is derived for the detection error probability as a function of signal-to-noise ratio at the detector input. The sensitivity of the radio pulse detection (by signal-to-noise ratio) is shown to increase in proportion to the number of detectors.

scholarly journals Design of Enhanced Rotation Locked Loop for Roll Angle Estimation of Rotating Vehicle in a Weak GPS Signal Environment

Sensors ◽  
2018 ◽  
Vol 19 (1) ◽  
pp. 80
Author(s):  
Hun Im ◽  
Deok Lim ◽  
Sang Lee
Keyword(s):  
Computer Simulations ◽  
Signal To Noise Ratio ◽  
Signal Strength ◽  
Roll Angle ◽  
Weak Signal ◽  
Signal To Noise ◽  
Angle Estimation ◽  
Signal Environment ◽  
Noise Ratio

In order to estimate the roll angle of a rotating vehicle, an enhanced rotation locked loop (RLL) algorithm is proposed in this paper. The RLL algorithm estimates the roll angle by using the property that the power of the GPS signal measured at the receiver of a rotating vehicle changes periodically. However, in case the received GPS power is decreased, the performance of the conventional RLL algorithm degrades, or it cannot estimate the roll angle anymore, therefore, for operating the RLL algorithm in a weak signal environment, this paper designs a method to increase the signal-to-noise ratio (SNR) by overlapping multiple GPS signals’ correlator outputs and a method to compensate the decreased response of a rotation discriminator at low-signal strength. Through computer simulations, the performance of the proposed algorithm is verified and it is shown that the roll angle can be estimated stably even at a weak signal environment down to 29 dB–Hz of C/N0.

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.

Automatic detection of bioacoustics impulses based on kurtosis under weak signal to noise ratio

2010 ◽  
Vol 71 (11) ◽  
pp. 1020-1026 ◽  
Author(s):  
C. Gervaise ◽  
A. Barazzutti ◽  
S. Busson ◽  
Y. Simard ◽  
N. Roy
Keyword(s):  
Signal To Noise Ratio ◽  
Automatic Detection ◽  
Weak Signal ◽  
Signal To Noise ◽  
Noise Ratio

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.

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