• The Journal of the Acoustical Society of Korea
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• v.43 no.1
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• pp.78-88
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• 2024

Ship-radiated noise received by passive sonar that can measure underwater noise can be identified and classified ship using Detection of Envelope Modulation on Noise (DEMON) analysis. However, in a low Signal-to-Noise Ratio (SNR) environment, it is difficult to analyze and identify the target frequency line containing ship information in the DEMONgram. In this paper, we conducted a study to extract target frequency lines using semantic segmentation among deep learning techniques for more accurate target identification in a low SNR environment. The semantic segmentation models U-Net, UNet++, and DeepLabv3+ were trained and evaluated using simulated DEMONgram data generated by changing SNR and fundamental frequency, and the DEMONgram prediction performance of DeepShip, a dataset of ship-radiated noise recordings on the strait of Georgia in Canada, was compared using the trained models. As a result of evaluating the trained model with the simulated DEMONgram, it was confirmed that U-Net had the highest performance and that it was possible to extract the target frequency line of the DEMONgram made by DeepShip to some extent.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.8
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• pp.1076-1082
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• 2018

This paper describes interferometer direction finder which measures the angle of arrival based on calculation of the phase difference of received radio signal from different antennas. Modern Electronic Warfare direction finder uses digital phase difference measuring techniques which have less effect on temperature variation and better performance under low Signal to Noise Ratio environment. In this paper, we analyze acceptable phase difference error for requirement of system's direction finding accuracy and introduce digital phase difference calculation techniques. We have investigated quantitative analysis on phase difference calculation according to sample number, SNR, interference injection. Through the simulation, frequency domain measurement technique is better performance than the time domain one at the environment of low SNR and interference injection. Proposed method can be used to determine the performance of interferometer direction finder.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.2
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• pp.962-977
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• 2019

The human voice is a convenient method of information transfer between different objects such as between men, men and machine, between machines. The development of information and communication technology, the voice has been able to transfer farther than before. The way to communicate, it is to convert the voice to another form, transmit it, and then reconvert it back to sound. In such a communication process, a vocoder is a method of converting and re-converting a voice and sound. The CELP (Code-Excited Linear Prediction) type vocoder, one of the voice codecs, is adapted as a standard codec since it provides high quality sound even though its transmission speed is relatively low. The EVRC (Enhanced Variable Rate CODEC) and QCELP (Qualcomm Code-Excited Linear Prediction), variable bit rate vocoders, are used for mobile phones in 3G environment. For the real-time implementation of a vocoder, the reduction of sound quality is a typical problem. To improve the sound quality, that is important to know the size and shape of noise. In the existing sound quality improvement method, the voice activated is detected or used, or statistical methods are used by the large mount of data. However, there is a disadvantage in that no noise can be detected, when there is a continuous signal or when a change in noise is large.This paper focused on finding a better way to decrease the reduction of sound quality in lower bit transmission environments. Based on simulation results, this study proposed a preprocessor application that estimates the SNR (Signal to Noise Ratio) using the spectral SNR estimation method. The SNR estimation method adopted the IMBE (Improved Multi-Band Excitation) instead of using the SNR, which is a continuous speech signal. Finally, this application improves the quality of the vocoder by enhancing sound quality adaptively.

• The Journal of the Acoustical Society of Korea
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• v.29 no.7
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• pp.468-474
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• 2010

The major factor that disturbs practical use of speech recognition is distortion by the ambient and channel noises. Generally, the ambient noise drops the performance and restricts places to use. DSR (Distributed Speech Recognition) based speech recognition also has this problem. Various noise cancelling algorithms are applied to solve this problem, but loss of spectrum and remaining noise by incorrect noise estimation at low SNR environments cause drop of recognition rate. This paper proposes methods for speech enhancement. This method uses MMSE-STSA for noise cancelling and ideal binary mask to compensate damaged spectrum. According to experiments at noisy environment (SNR 15 dB ~ 0 dB), the proposed methods showed better spectral results and recognition performance.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.7
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• pp.782-790
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• 2014

In this paper, we apply the 2-D Matrix Pencil Method(MPM) to the estimation of the direction of arrival(DOA) of multiple signals of interest(SOIs) in bistatic MIMO radar. The 2-D MPM shows remarkable performance under a low SNR environment and low computational complexity to estimate the DOA of multiple SOIs. Also, it is possible to estimate the direction of departure(DOD) which is an angle from transmitter to target. To verify the proposed algorithm, we applied the proposed algorithm to a uniformly spaced linear array(ULA) and compared the RMSE(Root Mean Square Error) of DOA and DOD under the various SNR with those of the 2-D Capon algorithm.

• Journal of KIISE
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• v.44 no.7
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• pp.733-741
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• 2017

LPWAN(Low Power Wide Area Network) technology is M2M (Machine to Machine) networking technology for the Internet of Things. The technology is designed to support low-power, long-distance and low-speed communications that are typical of LoRaWAN(Long Range Wide Area Network). To exchange inter-object information using a LoRaWAN, the link performances for various environments must be known. however, active performance analysis research that is based on an empirical environment is nonexistent. Therefore, this paper empirically evaluates the performance of the LoRa (Long Range) link, a physical communication technology of the LoRaWAN for various variables that may affect the link quality in indoor and outdoor environments. To achieve this, a physical performance monitoring system was designed and implemented. A communication experiment environment was subsequently constructed based on the indoor and outdoor conditions. The SNR(Signal to Noise Ratio), RSSI(Received Signal Strength Indication), and the PDR(Packet Delivery Ratio) were evaluated.

• The Journal of the Acoustical Society of Korea
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• v.24 no.1
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• pp.43-51
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• 2005

In this paper, we propose an algorithm that improves a tone quality of a noisy audio signal in order to enhance a Performance of perceptual filter using noise energy control. Most of the algorithms which were proposed by the other researchers usually applied a filter using the noise energy acquired from a silent range. In this case. the improvement rate of tone quality decreases if the noise energy is changed by the magnitude or environment variation in a signal frame. But the Proposed method Provides the means to find a food estimated noise through energy control of the estimated noise which is obtained from a silent range. Also we can get the enhancement of tone qualify in low frequency band unlike other methods. To show the performance of the Proposed algorithm, various input signals which had a different signal-to-noise ratio (SNR) such as 5dB, l0dB, 15dB and 20dB were used to test the proposed algorithm. With the proposed algorithm, we could confirm the enhancement of tone quality in terms of segmental SNR (SSNR). noise-to-mask ration (NMR) and mean opinion score (MOS) test.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.5 no.3
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• pp.443-449
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• 2001

This paper is simulation research to improve speech recognition rates under the noisy environment. We examines recognition ratio based on frequency-weighted HMM together with spectral subtraction. As results, frequency-weighted HMM with scaling coefficients is trained as a minimum error classification criterion, and is presents a higher recognition rates in noisy condition than a conventional method. Furthermore, spectral subtraction method gives 11 to 28% improvements for this frequency-weighted HMM in low SNR, and gives recognition rates of 81.7% at 6dB SNR of noisy speech.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.3
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• pp.411-416
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• 2003

In this paper, We analysed performance of adaptive modulation system with STTD. Transmission error of system is increased by ISI according to delay wave in wireless channel environment. Therefore, We analysed performance that it is applied adaptive modulation system with STTD to reduce ISI's effect. As a results, Data transmission of high speedㆍhigh quality could know possible by applying adaptive modulation system with STTD. Because of selected high modulation mode in low SNR.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.23 no.4
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• pp.950-956
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• 1998

In this paper, we investigate the effects of impulsive noise on the DS/SSMA system using TCM. We obtain the bound on the probability of bit error of the system, considering bothing impulsive noise and Rician fading, which are unavoidable in mobile communication environments. it turns out that we can achieve some coding gain by using TCM under impulsive noise environment. It is observed that the bit error probability is dominated by the background noise variance when the SNR is low and by the tail noise variance when the SNR is high.