• Journal of Satellite, Information and Communications
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• v.12 no.1
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• pp.28-33
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• 2017

In this paper, new signal model for bio-signal detection, i.e heart beat and respiration, using CW radar. Most research on this similar topic are based on the conventional signal model which is not correct in envisaging reflected signal from the human body. The system developed based on this conventional model can not predict exact performance of the system. So in this paper modified signal model for bio-radar is proposed and then simulation for detecting heartbeat and respiration signal in AWGN, multipath environment. The detection performance difference between two signal models are discussed.the modified

• Proceedings of the Optical Society of Korea Conference
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• 2003.02a
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• pp.158-159
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• 2003

In four-wave-mixing wavelength converter, we investigated the performance through simulation by using VPI tool, changing the input signal power and CW power at 2.SGb／s. Controlling optimal CW power to each input signal power, we extended the input signal power range to 20dB, which guarantees the minimum power penalty.

• The Journal of the Acoustical Society of Korea
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• v.23 no.7
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• pp.514-520
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• 2004

There are many techniques for underwater source localization. These are the methods based on TDOA (Time Difference Of Arrival) estimation. beamforming techniques and high resolution techniques, etc. In this Paper we estimate the underwater source position using MCPSP (Modified Cross Power Spectrum Phase) function that is calculated on frequency domain using sensors of small number. However, the performances of the localizing method based on MCPSP function drops greatly in the case of CW (Continuous Wave) signal . In this Paper we proposed the TDOA estimation method for pulsed CW signal. In the Proposed method we composed of new segment including a edge of ping. This segment was computed by short-time energy detection. With theoretical representation the performances of the proposed method were analyzed under various environment.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.866-869
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• 2015

In this paper, we propose a device for detect front object using low-price the CW Doppler sensor to prevent safety accident such as a bicycle, an electric wheelchair users. For this propose, we develop a signal process board and the object motion detect algorithm using to analyzing output signal of the CW Doppler sensor. Output signal from CW Doppler sensor is analog I and analog Q. The CW Doppler sensor shows phase I and phase Q of object differently when the object approach, stop, drop by sensor. We develop an algorithm that can detect object by discrimination information of phase using the CW Doppler sensor. The verification use firmware of applied hardware and algorithm. Then, the motion information can be confirming output depending on motion object by experiment normally. As a result, we check that the sensing information output by following motion of object and confirm an algorithm and motion of signal processing board.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.48 no.10
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• pp.60-66
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• 2011

In this paper, we analyze the effects of estimation error in the active cancellation signal, which is intended to counter the pulsed-CW signal of a hostile radar. We also examine the effects of estimation error in maximum-likelihood estimation (MLE) and quadratic interpolation scheme from a radar signal active cancellation viewpoint. Then, we modify the correlation-based error compensation scheme which mitigates the estimation error of MLE to improve the performance of the active cancellation signal. Finally, we present simulation results to show that the correlation-based scheme has better performance than the other in terms of radar signal active cancellation.

• IEMEK Journal of Embedded Systems and Applications
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• v.18 no.6
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• pp.277-283
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• 2023

Vital signals provide essential information regarding the health status of individuals, thereby contributing to health management and medical research. Present monitoring methods, such as ECGs (Electrocardiograms) and smartwatches, demand proximity and fixed postures, which limit their applicability. To address this, Non-contact vital signal measurement methods, such as CW (Continuous-Wave) radar, have emerged as a solution. However, unwanted signal components and a stepwise processing approach lead to errors and limitations in heart rate detection. To overcome these issues, this study introduces an integrated neural network approach that combines noise removal, demodulation, and dominant-frequency detection into a unified process. The neural network employed for signal processing in this research adopts a MLP (Multi-Layer Perceptron) architecture, which analyzes the in-phase and quadrature signals collected within a specified time window, using two distinct input layers. The training of the neural network utilizes CW radar signals and reference heart rates obtained from the ECG. In the experimental evaluation, networks trained on different datasets were compared, and their performance was assessed based on loss and frequency accuracy. The proposed methodology exhibits substantial potential for achieving precise vital signals through non-contact measurements, effectively mitigating the limitations of existing methodologies.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.19 no.11
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• pp.1204-1212
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• 2008

The paper proposes a new signal model which is revised from the commonly used signal model. Recently, many research institutions had a research about CW bio-radar for detecting he heartbeat and respiration. However, when the bio-radar detects the heartbeat using the previous signal model, the bio-radar has a disadvantage of weakness about he residual phase and AWGN. Also, the model is inappropriate in ergonomics because this signal model supposes hat the heart and lung are located at a same place. In this paper, the modified signal model, which is appropriate n ergonomics, is proposed. This paper analyzes and compares with the performance for detecting the heartbeat and respiration using the previous model and revised model in AWGN and multi-path environment.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.10 no.7
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• pp.1104-1110
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• 1999

When a FM-CW radar is used to measure the target distance, the nonlinearity relationship between the VCO control voltage and the output frequency makes an adverse effect on the measurement accuracy. Recently, many nonlinearity correction schemes using signal processing techniques and dedicated hardwares have been studied. This paper presents a signal processing technique to compensate for the VCO nonlinearity using a reference signal. To demonstrate the validity of the presented technique, several experiments were conducted and the results show reduction of the distortion in the range profile and the resolution improvement.

• Journal of the Korean Institute of Navigation
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• v.19 no.2
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• pp.115-120
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• 1995

Recently, the ship automation technology(SAT) has received great attention for the efficient management of the ship with minimum human efforts. Among the SAT, a distance measuring system, the key element is the signal processing unit for the interpretion of the received signal from the remote sensing of the oil tank. In this paper, the tank monitoring system using FM-CW is described for the oil tank level guage measurement with an emphsis of signal processing unit.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.8A
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• pp.763-770
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• 2002

Recognition of CW Morse signals can be divided into several phases such as detection of tones and spaces, signal processing for removing noise from detected signals, decision of tones/spaces, mapping a sequence of tones and spaces into characters, error correction of a character message with textual repetition. In this paper, in order to cope with signal fading effectively we propose a signal detection method of identifying peaks in the frequency domain and present techniques for combining multiple frequency peaks and for removing residual signal components and noise. LMS adaptive method is applied for decision of tones/spaces, and initial value setting and malfunctioning conditions are analyzed. In recognition experiments, we used CW Morse signals collected by radio receivers and found that the proposed method achieves good recognition performance even in severe fading conditions.