• Journal of Advanced Navigation Technology
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• v.13 no.4
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• pp.482-489
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• 2009

This paper proposes a CW(Continuous-Wave) bio-radar applying a new adaptive noise canceller based on ALE(Adaptive Line Enhancer) which can remove the Gaussian noise and system noise. Recently the research works on this CW bio-radar which can be used to detect heartbeat and respiration are advanced by the university and research facility. Although the researches describe CW bio-radar not only is vulnerable for the Gaussian noise but also has a disadvantage of decreasing the heart-rate accuracy due to the noise, the researches do not demonstrate the effective method for removing the noise component in a baseband signal. In this paper, a CW bio-radar applying the new adaptive noise canceller based on ALE which can remove the noise component is proposed. This paper compares and analyzes the performance for increasing the heart-rate accuracy according to removing the Gaussian noise and system noise in the baseband signal through the quadrature receiver which can alleviate the demodulation sensitivity to target position.

• 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

• 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.

• 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.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.7
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• pp.1532-1535
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• 2009

This paper describes a K-band CW radar transceiver suitable for power saving motion sensor. The presented transceiver module is designed and contains patch antennas, dielectric resonator oscillator (DRO), IF amplifier, mixer, divider. The designed divider and antenna are measured and the transmitting frequency and the power were fairly good for using in commercial applications. The transceiver is manufactured with a dimension of 35${\times}$35${\times}$10(mm) and can be adapted in various applications.

• 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.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.12
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• pp.2911-2916
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• 2015

The CCTV is limited by weather conditions. To overcome this limitation, we develop a monitoring program that can sense the approach or recede of two or more objects within a surveillance system that uses a continuous-wave (CW) Doppler radar, and we proposed an algorithm to efficiently detect the approach or recede information of the object. The proposed algorithm separates the signal received by the CW Doppler radar into the real and imaginary parts using Fast Fourier Transform (FFT), and sums the amplitudes for each frequency to determine whether the objects are approaching or receding, using their locations. The algorithm is verified by simulations and experiments, which confirms that it successfully detects the approach or recede of two objects.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.8
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• pp.1752-1758
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• 2010

A FM-CW radar is used for the various purposes as a remote sensing device since it has the advantages of the relatively simple implementation and the low probability of signal interception. A FM-CW radar uses the same frequency modulated continuous wave for both transmission and demodulation. Therefore, the received beat frequency represents the range and Doppler information of targets. However, using the conventional FFT method, the degree of accuracy and resolution in the spectrum estimation can be seriously degraded in the detection and tracking of fast moving targets because of the short dwell time. Therefore, in this paper, the model parameter estimation methods called as an autoregressive method is applied to overcome these problems and showed that the improved accuracy and resolution can be obtained for the target range and velocity estimation.

• 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.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.23 no.7
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• pp.815-821
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• 2012

A CW Doppler radar can measure radial velocity of an object. It detects a Doppler frequency shift that is proportioned to radial velocity of a moving object. To detect a Doppler frequency shift, FFT(Fast Fourier Transform) is conducted. In this process, the time domain received signal is transformed to a frequency domain. A number of FFT affects not only the time resolution but also signal to noise ratio of received signal. So finally it is related with a radial velocity accuracy. Therefore in this paper, it is described the relation of time resolution and the radial velocity accuracy.