• Current Optics and Photonics
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• v.2 no.5
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• pp.413-421
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• 2018

We propose a novel methodology based on the multiplication function to improve the signal-to-noise ratio (SNR) for vibration detection in a phi optical time-domain reflectometer system (phi-OTDR). The extreme-mean complementary empirical mode decomposition (ECEMD) is designed to break down the original signal into a set of inherent mode functions (IMFs). The multiplication function in terms of selected IMFs is used to determine a vibration's position. By this method, the SNR of a phi-OTDR system is enhanced by several orders of magnitude. Simulations and experiments applying the method to real data prove the validity of the proposed approach.

• Journal of Radiation Protection and Research
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• v.42 no.4
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• pp.197-204
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• 2017

Background: X-ray imaging detectors for the nondestructive cargo container inspection using MeV-energy X-rays should accurately portray the internal structure of the irradiated container. Internal and external factors can cause noise, affecting image quality, and scattered radiation is the greatest source of noise. To obtain a high-performance transmission image, the influence of scattered radiation must be minimized, and this can be accomplished through several methods. The scatter rejection method using an anti-scatter grid is the preferred method to reduce the impact of scattered radiation. In this paper, we present an evaluation the characteristics of the signal and noise according to physical and material changes in the anti-scatter grid of the imaging detector used in cargo container scanners. Materials and Methods: We evaluated the characteristics of the signal and noise according to changes in the grid ratio and the material of the anti-scatter grid in an X-ray image detector using MCNP6. The grid was composed of iron, lead, or tungsten, and the grid ratio was set to 2.5, 12.5, 25, or 37.5. X-ray spectrum sources for simulation were generated by 6- and 9-MeV electron impacts on the tungsten target using MCNP6. The object in the simulation was designed using metallic material of various thicknesses inside the steel container. Using the results of the computational simulation, we calculated the change in the scatter-to-primary ratio and the signal-to-noise ratio improvement factor according to the grid ratio and the grid material, respectively. Results and Discussion: Changing the grid ratios of the anti-scatter grid and the grid material decreased the scatter linearly, affecting the signal-to-noise ratio. Conclusion: The grid ratio and material of the anti-scatter grid affected the response characteristics of a container scanner using high-energy X-rays, but to a minimal extent; thus, it may not be practically effective to incorporate anti-scatter grids into container scanners.

• ETRI Journal
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• v.29 no.5
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• pp.607-613
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• 2007

Most signal-to-noise ratio (SNR) estimation techniques in digital communication channels derive the SNR estimates solely from samples of the received signal after the matched filter. They are based on symbol SNR and assume perfect synchronization and intersymbol interference (ISI)-free symbols. In severe channel distortion where ISI is significant, the performance of these estimators badly deteriorates. We propose an SNR estimator which can operate on data samples collected at the front-end of a receiver or at the input to the decision device. This will relax the restrictions over channel distortions and help extend the application of SNR estimators beyond system monitoring. The proposed estimator uses the characteristics of the second order moments of the additive white Gaussian noise digital communication channel and a linear predictor based on the modified-covariance algorithm in estimating the SNR value. The performance of the proposed technique is investigated and compared with other in-service SNR estimators in digital communication channels. The simulated performance is also compared to the Cram$\acute{e}$r-Rao bound as derived at the input of the decision circuit.

• ETRI Journal
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• v.33 no.2
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• pp.176-183
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• 2011

This paper presents a new analytical approach and experimental verification for the improvement of noise performance in phased-array receivers. For analysis purposes, a multi-channel array system is converted into an equivalent single-channel system, such that the two presents the identical signal and noise powers at the output, respectively. We define an effective gain, noise figure, and signal-to-noise ratio in the equivalent system. Through the proposed approach, the noise performance of the array receiver is analyzed in a general and straightforward manner and then compared to that of each individual array channel. In addition, the phase noise of the array system is analyzed in a rigorous manner, showing its effective reduction by a factor of the array size. The predicted improvement of the noise performance is experimentally confirmed with a CMOS integrated phased-array receiver.

• Journal of Astronomy and Space Sciences
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• v.35 no.4
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• pp.279-286
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• 2018

Radar sensors are used for space situational awareness (SSA) to determine collision risk and detect re-entry of space objects. The capability of SSA radar system includes radar sensitivity such as the detectable radar cross-section as a function of range and tracking capability to indicate tracking time and measurement errors. The time duration of the target staying in a range cell is short; therefore, the signal-to-noise ratio cannot be improved through the pulse integration method used in pulse-Doppler signal processing. In this study, a method of improving the signal-to-noise ratio during range migration is presented. The improved detection performance from signal processing gains realized in this study can be used as a basis for comprehensively designing an SSA radar system.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.6
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• pp.1249-1256
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• 2019

In this paper, we propose a new algorithm to remove acoustic feedback and noise in hearing aids. Instead of using the conventional FIR structure, this algorithm is a deep learning algorithm using neural network adaptive prediction filter to improve the feedback and noise reduction performance. The feedback canceller first removes the feedback signal from the microphone signal and then removes the noise using the Wiener filter technique. Noise elimination is to estimate the speech from the speech signal containing noise using the linear prediction model according to the periodicity of the speech signal. In order to ensure stable convergence of two adaptive systems in a loop, coefficient updates of the feedback canceller and noise canceller are separated and converged using the residual error signal generated after the cancellation. In order to verify the performance of the feedback and noise canceller proposed in this study, a simulation program was written and simulated. Experimental results show that the proposed deep learning algorithm improves the signal to feedback ratio(: SFR) of about 10 dB in the feedback canceller and the signal to noise ratio enhancement(: SNRE) of about 3 dB in the noise canceller than the conventional FIR structure.

• Journal of Korean Ophthalmic Optics Society
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• v.17 no.2
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• pp.203-207
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• 2012

Purpose: Electroretinogram(ERG) signal noise as well as conducting other bio-signal measurement were generated. It was intened to enhance the accuracy of retinal-related diagnosis with removing signal noise. Methods: Sampling signal was made with generating 60 Hz noise and white noise. The noise were removed using wavelet transforms and bandpass filter. De-noising frequency was compared with Fourier transform spectrum. Removed noises were compared numerically using SNR(signal to noise ratio). Results: The result compared Fourier transform spectrum was showed that 60 Hz noise removed completely and most of white noise was removed by wavelet transforms. 60 Hz and the white noise remained using bandpass filters. The result compared SNR showed that wavelet transforms was 22.8638 and bandpass filter was 4.0961. Conclusions: Wavelet transform showed less signal distortion in removing noise. ERG signal is expected to improve the accuracy of retinal-related diagnosis.

• Journal of Integrative Natural Science
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• v.13 no.3
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• pp.92-96
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• 2020

Taguchi's robust parameter design is an approach to reduce the performance variation of quality characteristics in products and processes. In robust design, the signal-to-noise ratio (SN ratio) was used to find the optimum condition to minimize the variation of quality characteristics as much as possible and bring the average of quality characteristics closer to the target value. In this paper, we propose a simultaneous optimization method based on a linear model of the SN ratio as a method to find the optimal condition of the control factor in case of multi-characteristics. In addition, the proposed method and the existing method were compared and studied by taking actual cases.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.5
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• pp.38-43
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• 1996

Windowing routines have as their purpose the reduction of the sidelobes of a spectral output of the FFT or DFT routines. Windowing routines accomplish this by forcing the beginning and end of any sequence to approach each other in value. Since they must work with any sequence they force the beginning and ending samples near zero. To make up for this reduction in power, windowing routines give extra weight to the values near the middle of the sequence. The difference between windows is the way in which they transition from the low weights near the edges to the higher weights neqr the middle of the sequence. Signal-to-noise ratio(SNR) can be determined by the ratio of the output noisy signal variance to the input noisy signal variance of a window. Standard deviation of noise is reduced by windowing. Thus, the windowing operation improved the SNR of the noisy signal. This paper shows a performance estimation of windowing on a single tone with added Gaussian noise and uniform noise.

• Journal of Advanced Navigation Technology
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• v.25 no.5
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• pp.357-362
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• 2021

UWB(ultra wide band) communication systems employ short pulses to transmit information which spreads the signal energy over a very wide frequency spectrum. Received signal-to-noise power ratio of UWB signals is an important factor in determining the accuracy of a positioning system. As the signal to noise power ratio gets higher, positioning errors decrease since noise becomes less effective. Calculation of signal to noise power ratio as a function of communication distance provides important guidelines for the system design. And the performance of a positioning system also depends heavily on the channel model. As a result of the analysis, it was found that the performance of the received signal to noise power ratio according to the communication distance was better in the LOS channel environment than in the Non LOS(line of sight) channel environment. And as the symbol interval of the preamble signal increases at a specific communication distance, the channel capacity of the UWB system increases.