• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.05a
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• pp.605-608
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• 2009

It is necessary to estimate the Doppler spectrum for each range cell for the extraction of useful information from the return echoes in radar systems used for the remote sending purpose. However, The conventional spectrum estimation method, FFT(Fast Fourier Transform), called the Doppler filter bank, causes the frequency resolution problem if the dwell time is relatively short. This short acquisition time also spreads the side lobe levels of return echoes further, resulting in difficulties for the discrimination of weak target signals included in relatively strong target echoes. Therefore, in this paper, the efficient Doppler spectrum estimation methods are compared and investigated through the parameter spectrum estimation in the time domain to overcome these problems.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.3
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• pp.393-398
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• 2022

During the test operation period of the wind profiler prototype, radio frequency interference (RFI) contamination occurred in the spectrum. The reference of the RFI that removed the algorithm appearing in the wind profiler spectrum were investigated, and a new algorithm was developed to remove the RFI. First, it was filtered with a threshold value of 0.1 m/s of the spectral width, and the range of the number of gates with the same radial velocity was determined according to whether the beam was a vertical beam or an oblique beam. RFI contamination was removed through filtering and scanning of non-weather signals, and the continuity of wind vectors calculated from the improved spectral radial velocity was verified.

• The Journal of Engineering Geology
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• v.27 no.3
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• pp.217-231
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• 2017

The subsidence of ground in urban area can be caused by the occurrence of the cavity and the change in ground volumetric water content. The objective of this study is the detection of abnormal area of ground in urban area where the cavity or the change in ground volumetric water content is occurred by the ground penetrating radar signal. GPR survey is carried out on the test bed with a circular buried object. From the GPR survey, the signals filtered by the bandpass filtering are measured, and the methods consisting of gain function, time zero, background removal, deconvolution and display gain are applied to the filtered signals. As a result of application of the signal processing methods, the polarity of signal corresponds with the relation of electrical impedance of the cavity and the ground in test bed. In addition, the relative permittivity calculated by GPR signal is compared with that of predicted by volumetric water content of the test bed. The relative permittivities obtained from two different methods show similar values. Therefore, the abnormal area where the change in ground volumetric water content is occurred can be detected from the results of the GPR survey in case the depth of underground utilities is known. Signal processing methods and estimation of relative permittivity performed in this study may be effectively used to detect the abnormal area of ground in urban area.

• Geophysics and Geophysical Exploration
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• v.25 no.4
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• pp.189-200
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• 2022

Ground subsidence on urban roads is a social issue that can lead to human and property damages. Therefore, it is crucial to detect underground cavities in advance and repair them. Underground cavity detection is mainly performed using ground penetrating radar (GPR) surveys. This process is time-consuming, as a massive amount of GPR data needs to be interpreted, and the results vary depending on the skills and subjectivity of experts. To address these problems, researchers have studied automation and quantification techniques for GPR data interpretation, and recent studies have focused on deep learning-based interpretation techniques. In this study, we described a hyperbolic event detection process based on deep learning for GPR data interpretation. To demonstrate this process, we implemented a series of algorithms introduced in the preexisting research step by step. First, a deep learning-based YOLOv3 object detection model was applied to automatically detect hyperbolic signals. Subsequently, only hyperbolic signals were extracted using the column-connection clustering (C3) algorithm. Finally, the horizontal locations of the underground cavities were determined using regression analysis. The hyperbolic event detection using the YOLOv3 object detection technique achieved 84% precision and a recall score of 92% based on AP50. The predicted horizontal locations of the four underground cavities were approximately 0.12 ~ 0.36 m away from their actual locations. Thus, we confirmed that the existing deep learning-based interpretation technique is reliable with regard to detecting the hyperbolic patterns indicating underground cavities.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.11
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• pp.66-70
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• 2016

This paper presents an 24 GHz I/Q LO generator for a heartbeat measurement radar system. In order to improve the mismatch performance between I and Q LO signals against process variation, a 24 GHz I/Q LO generator employing a low-pass phase shifter and a high-pass phase shifter composed of inductors and capacitors is proposed. The proposed 24 GHz I/Q LO generator consists of an LO buffer, a low-pass phase shifter and a high-pass phase shifter. It was designed using a 65 nm CMOS technology and draws 8 mA from a 1 V supply voltage. The proposed 24 GHz I/Q LO generator shows a gain of 7.5 dB, a noise figure of 2.3 dB, 0.1 dB gain mismatch and $4.3^{\circ}$ phase mismatch between I and Q-path against process and temperature variations for the operating frequencies from 24.05 GHz to 24.25 GHz.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.26 no.2
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• pp.218-225
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• 2015

Inverse synthetic aperture radar(ISAR) is coherent imaging system formed by conducting signal processing of received data which consists of radar cross section(RCS) reflected from maneuvering target. A novel algorithm is proposed to compensate inter-pulse motion(IPM) for the purpose of forming an well-focused ISAR image through signals generated by stepped chirp waveform( SCW). The velocity and acceleration of the target related to IPM are estimated based on particle swarm optimization (PSO) which has been widely used in optimization technique. Furthermore, a modified PSO which enables us to improve the performance of PSO is used to compensate IPM in a very short-time. Simulation results using point scatterer model of a Boeing-737 aircraft validate the performance of the proposed algorithm.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.22 no.10
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• pp.981-989
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• 2011

In this paper, we performed radar target classification for the five scale models using ultra-wideband measured signal. In order to compare the performance, the 2 GHz(2~4 GHz), 4 GHz(2~6 GHz), and 6 GHz(2~8 GHz) bandwidth were used. Short time Fourier transform(STFT) and continuous wavelet transform(CWT) are used for target feature extraction. Extracted feature vectors are used as input for the multi-layerd perceptron(MLP) neural network classifier. The results show that as the bandwidth is wider, the performance is better.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.12
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• pp.1284-1291
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• 2014

For detection and parameter estimation, a multicarrier radar should discriminate a channel containing jamming signal and either leave it out or regenerate jammer suppressed target signal. To discriminate jamming channels, we use the angular spectrum of an eigenvector that embeds target echoes and jamming signals. We propose a criteria to discriminate the jammer channels and its basis through mathematical analysis. Moreover, we show some procedures to regenerate the jammer suppressed target echoes. Finally, the validity of the proposed method is demonstrated through simulation results showing improved performance in terms of direction of arrival(DOA) estimation.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.28 no.3
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• pp.186-194
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• 2017

In this paper, we analyze the main performance of satellite's Synthetic Aperture Radar system for high resolution and wide swath. We have used the radiation pattern of reflector antenna with array feed and comparison between the conventional ScanSAR mode and SweepSAR mode has been carried out. The SweepSAR mode is a high-resolution wide-swath mode that transmits beams over a wide range and receives echo signals through sequential beamforming based on SCORE(SCan On REceive). In this paper, we analyzed the operating principle and characteristics of satellite's SweepSAR mode and simulate system performances. In addition, in order to increase the utilization of image, performances analysis for multiple frequency bands(C-band, X-band) has been considered.

• Journal of the Korean Society of Industry Convergence
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• v.23 no.3
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• pp.433-444
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• 2020

This study proposes a method to improve the sleep stage and efficiency estimation of sleep apnea patients using a UWB (Ultra-Wideband) radar. Motion and respiration extracted from the radar signal were used. Respiratory signal disturbances by motion artifacts and irregular respiration patterns of sleep apnea patients are compensated for in the preprocessing stage. Preprocessing calculates the standard deviation of the respiration signal for a shift window of 15 seconds to estimate thresholds for compensation and applies it to the breathing signal. The method for estimating the sleep stage is based on the difference in amplitude of two kinds of smoothed respirations signals. In smoothing, the window size is set to 10 seconds and 34 seconds, respectively. The estimated feature was processed by the k-nearest neighbor classifier and the feature filtering model to discriminate between the sleep periods of the rapid eye movement (REM) and non-rapid eye movement (NREM). The feature filtering model reflects the characteristics of the REM sleep that occur continuously and the characteristics that mainly occur in the latter part of this stage. The sleep efficiency is estimated by using the sleep onset time and motion events. Sleep onset time uses estimated features from the gradient changes of the breathing signal. A motion event was applied based on the estimated energy change in the UWB signal. Sleep efficiency and sleep stage accuracy were assessed with polysomnography. The average sleep efficiency and sleep stage accuracy were estimated respectively to be about 96.3% and 88.8% in 18 sleep apnea subjects.