• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.1
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• pp.70-76
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• 2019

Ultra Wideband (UWB) Radar is a high-resolution radar for short distance detection which uses signals transmitted and received by each antennas in order to detect a target. It is possible to detect the respiration and heartbeat of a person without contact It is getting more and more often utilized since it is not affected by physical environment. In this paper, we implement an algorithm to detect human respiration and heartbeat rate using UWB radar signal. We process radar signals reflected from human body using Median filter, Kalman filter, Band Pass filter and so on. We also use CZT to extract breathing and heart rate. ECG (Electrocardiogram) was used for comparison of heartbeat data and we confirm that each data of ECG and UWB Radar were more than 98% identical each other.

• Journal of Convergence for Information Technology
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• v.8 no.5
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• pp.137-143
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• 2018

Generally, a radar signal is modulated and transmitted in order to avoid signal detection. In electronic warfare, the specification of a radar is recognized by analysing the received radar pulses. In this paper, we propose an algorithm to recognize the PRI (Pulse Repetition Interval) type of radar signals. This algorithm uses the autocorrelation technique applying different comparison ranges according to the PRI type. It applies a short comparison window to stable and staggered PRI, and a relatively large comparison range to jittered PRI. The experiment shows that the proposed algorithm can discriminate the PRI type of radar pulses correctly. For the more, it can find out the stagger level of staggered type of radar signals.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.6
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• pp.124-132
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• 2011

In a modern electronic warfare, radar signal environments become more denser and complex. Therefor the capability of reliable signal analysis techniques is required for ES(Electronic warfare Support) system to identify and analysis individual emitter signals from received signals. In this paper, we propose the new signal grouping algorithm to ensure the reliable signal analysis and to reduce the cost of the signal processing steps in the ES. The proposed grouping algorithm uses KDE(Kernel Density Estimator) and its CDF(Cumulative Distribution Function) to compose windows considering the statistical distribution characteristics based on the radar frequency modulation type. Simulation results show the good performance of the proposed technique in the signal grouping.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.6
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• pp.372-377
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• 2003

Many of modem radars use modulated pulse repetition intervals for the purpose of anti-aliasing and ECCM. The interception, analysis and identification of radar signals is a major function of a radar intercept receiver. In this paper, we discuss the identification of pulse repetition intervals modulation of radar signals which is one of the major parameters for the analysis of radar. We proposed a new algorithm based on Markov models approach. This approach is shown to be reliable and robust to the missing pulses, as well as to require only relatively few pulse data.

• Journal of Satellite, Information and Communications
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• v.12 no.3
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• pp.63-68
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• 2017

SAR(Synthetic Aperture Radar) uses electromagnetic signals to acquire ground information and has been used for wide coverage reconnaissance missions regardless of weather conditions. However SAR is known to be vulnerable to interference signals by other communication devices or radar instruments and may suffer from undesirable performance degradations and image quality. In this paper, a modified Eigen-subspace based filter is proposed that can be easily applied to SAR images affected by interference signals. The method of constructing Eigen-subspace based filter is briefly described and various simulations are performed to show the performance of the interference mitigation process. The suppression filter is applied to a ALOS PALSAR raw data affected by interfering signals in order to verify its superiority over the Notch filter.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.8
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• pp.3862-3879
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• 2019

More and more problems for public security have occurred due to the limited solutions for drone detection especially for micro-drone in long range conditions. This paper aims at dealing with drones detection using a radar system. The radio frequency (RF) signals emitted by a controller can be acquired using the radar, which are usually too weak to extract. To detect the drone successfully, the static clutters and linear trend terms are suppressed based on the background estimation algorithm and linear trend suppression. The principal component analysis technique is used to classify the noises and effective RF signals. The automatic gain control technique is used to enhance the signal to noise ratios (SNR) of RF signals. Meanwhile, the empirical mode decomposition (EMD) based wavelet transform (WT) is developed to decrease the influences of the Gaussian white noises. Then, both the azimuth information between the drone and radar and the bandwidth of the RF signals are acquired based on the statistical analysis algorithm developed in this paper. Meanwhile, the proposed accumulation algorithm can also provide the bandwidth estimation, which can be used to make a decision accurately whether there are drones or not in the detection environments based on the probability theory. The detection performance is validated with several experiments conducted outdoors with strong interferences.

• Journal of Advanced Navigation Technology
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• v.26 no.2
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• pp.85-90
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• 2022

In this study, in order to test the performance of the aircraft system, a threat signal simulator that can transmit a signal similar to the actual threat to the aircraft under test with high power was designed. The high-power threat signal simulator should be able to transmit broadband (UHF band, L band, S band, X band) communication signals and radar signals, and control to transmit signals accurately directed to the aircraft through interfacing tracking radar. The signal strength of the developed equipment is 63 dBm to 93 dBm or more depending on type of signal, and the tracking precision is less than 0.1 degree, which satisfies the required performance. And it was confirmed that the antenna of the high-power threat signal simulator can accurately direct the signal to the aircraft position through the tracking radar interfacing.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.357-359
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• 2009

In this paper, the 2.4GHz doppler radar system consisting of the doppler radar module and a baseband module were designed to detect heartbeat and respiration signal without direct skin contact. A bio-radar system emits continuous RF signal of 2.4GHz toward human chest, and then detects the reflected signal so as to investigate cardiopulmonary activities. The heartbeat and respiration signals acquired from quadrature signal of the doppler radar system are applied to the pre-processing circuit, amplification circuit, and the offset circuit of the baseband module. ECG(electrocardiogram) and reference respiration signals are measured simultaneously to evaluate the doppler radar system. As a result, the respiration signal of doppler radar signal is detected to 1m without complex digital signal processing. The sensitivity and calculated from I/Q respiration signal were $98.29{\pm}1.79%$, $97.11{\pm}2.75%$, respectively, and positive predictivity were $98.11{\pm}1.45%$, $92.21{\pm}10.92%$, respectively. The sensitivity and positive predictivity calculated from phase and magnitude of the doppler radar were $95.17{\pm}5.33%$, $94.99{\pm}5.43%$, respectively. In this paper, we confirmed that noncontact real-time heartbeat and respiration detection using the doppler radar system has the possibility and limitation.

• Journal of Multimedia Information System
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• v.5 no.4
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• pp.245-256
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• 2018

This study estimated rainfall information more effectively by image signals through the information system of weather radar. Based on this, we suggest the way to estimate quantitative precipitation utilizing overlapped observation area of radars. We used the overlapped observation range of ground hyetometer observation network and radar observation network which are dense in our country. We chose the southern coast where precipitation entered from seaside is quite frequent and used Sungsan radar installed in Jeju island and Gudoksan radar installed in the southern coast area. We used the rainy season data generated in 2010 as the precipitation data. As a result, we found a reflectivity bias between two radar located in different area and developed the new quantitative precipitation estimation method using the bias. Estimated radar rainfall from this method showed the apt radar rainfall estimate than the other results from conventional method at overall rainfall field.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.11
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• pp.3121-3129
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• 2009

Conventional marine radar systems utilize pulse radar which is capable of high-power transmissions and is effective for remote detection purposes. A pulse radar is most commonly used on medium or large vessels due to its expensive installation and maintenance costs. I propose the use of a Frequency Modulated Continuous Wave (FMCW) radar system operated at low-power and high-resolution instead of the conventional pulse-radar based system. The transmitted and received signals of the FMCW radar system were theoretically analyzed and radar signal processing design and simulation experiments were performed to detect the range and speed. Intermediate Frequency (IF) signal mixed with virtual transmit and receive signals were generated to perform FMCW radar signal processing simulations where the IF signal underwent noise reduction through a lowpass filter. The maximum frequency was derived through the sample interval of the FFT size instead of using A/D converter. This maximum frequency was used to get the frequency range and frequency speed which were in turn used to calculate the range and speed. The virtual beat frequency generated using MATLAB is utilized to analyze the beat frequency used in the actual FMCW radar system signal processing. The differences in the range and speed of the beat frequency signals are processed and analyzed.