• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.44 no.2
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• pp.131-138
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• 2016

In this paper, we studied the IRF performances of the chirp signal used in the SAR system. The most important factors that degrade IRF performances are amplitude and phase errors. Each factor can be represented to linear, quadratic, random and ripple terms. That can be extracted by a quadratic polynomial curve fitting of chirp waveform. We analyzed the IRF performances by the error terms and supposed the minimum value of RF non-linearity to meet the specification of the PSLR and ISLR.

• Defense and Technology
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• no.9 s.295
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• pp.72-79
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• 2003

Northrop Grumman은 코만치의 TASS(Taget Acqusition System Software)를 책임지고 있는데 4가지 주요 기능을 가지고 있다. 즉 열상으로부터 목표물과 같은 물체를 찾는 목표물 감지/분류 지원, 'imager'나 TV FOV에 있는 1개의 주 목표와 5개의 2차 목표를 추적하는 자동 목표 추적기, 탑재 및 미탑재 신호원으로부터 모든 상대적 정보를 상호 연관시키는 목표물 위협 관리기 그리고 레이더 및 열상장비 출력상의 무언가를 비교하는 센서 융합이 바로 그것이다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.7
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• pp.151-157
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• 2019

Recently, monitoring respiration of people has been of interest using non-invasive method. Among the vital signals usually used for indicating health status, non-invasive and portable device based monitoring respiratory status is practically useful and enable one to promptly deal with abnormal physical status. This paper proposes the approach to real-time detection of apnea signal based on Short-Time-Fourier-Transform(STFT). Contrary to the analysis of a signal in frequency domain using Fast-Fourier Transform, this paper employs Short-time-Fourier-Transform so that frequency response can be analyzed in short time interval. The respiratory signal is acquired using UWB radar sensor that enables one to obtain respiration signal in contactless way. Detection of respiratory status is carried out by analyzing frequency response, and classification of respiratory status can be provided. In particular, STFT is employed to analyze respiratory signal in real-time, leading to effective analysis of the respiratory status in practice. In the case of existence of noise in the signal, appropriate filtering process is employed as well. The proposed method is straightforward and is workable in practice to analyze the respiratory status of people. To evaluate the proposed method, experimental results are provided.

• The Journal of Korean Institute of Next Generation Computing
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• v.13 no.4
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• pp.29-39
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• 2017

Various electronic warfare situations drive the need to develop an integrated electronic warfare simulator that can perform electronic warfare modeling and simulation on radar threats. In this paper, we analyze the components of a simulation system to reversely model the radar threats that emit electromagnetic signals based on the parameters of the electronic information, and propose a method to gradually maintain the reverse extrapolation model of RF threats. In the experiment, we will evaluate the effectiveness of the incremental model update and also assess the integration method of reverse extrapolation models. The individual model of RF threats are constructed by using decision tree, naive Bayesian classifier, artificial neural network, and clustering algorithms through Euclidean distance and cosine similarity measurement, respectively. Experimental results show that the accuracy of reverse extrapolation models improves, while the size of the threat sample increases. In addition, we use voting, weighted voting, and the Dempster-Shafer algorithm to integrate the results of the five different models of RF threats. As a result, the final decision of reverse extrapolation through the Dempster-Shafer algorithm shows the best performance in its accuracy.

• Korean Journal of Remote Sensing
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• v.21 no.4
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• pp.303-316
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• 2005

Strong radar returns were observed in oyster sea farms, and coherent interferometric pairs were successfully constructed. Tide height in coastal area is possible to be measured by using interferometric phase and intensity of SAR data. This SAR application technique for measuring the tide height in the near coastal zone can be further improved when applied to double bounce dominant areas. In this paper, we investigate the characteristics of polarimetric signature in the oyster farm structures. Laboratory experiments were carried out using Ku-band according to the target scale. Radar returns from vertical poles are stronger than those from horizontal Pole by 10.5 dB. Single bounce components were as strong as double bounce components and more sensitive to antenna look direction. Double bounce components show quasi-linear relation with the height of vertical poles, which implies double bounce is more useful to determine water level than total power. A L-band NASA/IPL airborne SAR (AIRSAR) image was classified into single-, double-bounce, and volume scattering components. It is observed that oyster farms are not always characterized by double bounced scattering. Double bounce is a main scattering mechanism in oyster farms standing above seawater, while single bounce is stronger than double bounce when bottom tidal flats are exposed to air. Ratios of the normalized single to double bounce components in the former and latter cases were 0.46 and 5.62, respectively. It is necessary to use double bounce dominant sea farms for tide height measurement by DInSAR technique.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39C no.12
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• pp.1267-1279
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• 2014

In this paper, we suggest the development of object detection systems for the safety of the ship through the study of the properties of short-range radar. Many of the short-range radars developed for special purpose like cars has cheaper price advantages but it is not proper to every application. In order to overcome such obstacles we need to analysis data from experiments in various environments and feature analysis of the device is essential. Also, the data clustering algorithms to display correct classified moving objects is necessary. In this paper we propose the advanced fast moving object detection system using short range radars with better detection accuracy. And we proposed a clustering algorithm using the value of the RCS and the speed and trajectory information of the radar data that are reflected.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.3
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• pp.251-256
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• 2019

In this paper we proposed system and algorithm to recognize hand gestures based on the millimeter wave that is in 65GHz bandwidth. The proposed system is composed of millimeter wave radar board, analog to data conversion and data capture board and notebook to perform gesture recognition algorithms. As feature vectors in proposed algorithm. we used global and local zernike moment descriptor which are robust to distort by rotation of scaling of 2D data. As Experimental result, performance of the proposed algorithm is evaluated and compared with those of algorithms using single global or local zernike descriptor as feature vectors. In analysis of confusion matrix of algorithms, the proposed algorithm shows the better performance in comparison of precision, accuracy and sensitivity, subsequently total performance index of our method is 95.6% comparing with another two mehods in 88.4% and 84%.

• Proceedings of the Korea Information Processing Society Conference
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• 2011.11a
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• pp.434-437
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• 2011

차세대 지능적 무기체계의 자동화를 목표로 SAR(Synthetic Aperture Radar) 영상 신호를 이용한 표적 인식률 향상을 위한 여러가지 방법들이 제안되어 왔다. 기존의 연구들은 SAR 영상의 고차원 특징을 그대로 사용했기 때문에 표적 인식의 성능저하가 있었다. 본 연구에서는 정보 획득 거리가 길고, 날씨에 제약이 없이 전천후 작전 운용이 가능하도록 레이더의 특징과 고해상도 영상을 결합한 SAR 이미지를 이용한 표적 인식률 향상 방법을 제안한다. 효과적인 표적 인식을 하기위해 고차원의 특징벡터를 저차원의 특징벡터로 축소하는 PCA(Principal Component Analysis)를 기반으로 하는 SVM(Support Vector Machine)을 사용한 표적 인식 기법을 사용하였고, PCA 기반의 SVM 분류기를 이용한 표적 인식이 SVM 만을 사용한 표적 인식보다 향상된 성능을 보인 것을 확인하였다.

• Journal of the Institute of Convergence Signal Processing
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• v.2 no.1
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• pp.12-18
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• 2001

SAR radar and FLIR images, which are taken from sensors on aircrafts or satellites, are compressed prior to transmission to facilitate rapid transfer through the limited bandwidth channels. In this case, it is important that it achieves compression ratio as high as possible as well as high target detection rate. In this paper a joint ATR-compression system based on the subband coding and VQ is proposed, which utilizes the encoder as a predictor or classifier for target detection. Simulation result shows that the proposed system achieves a relatively high level of target detection performance as well as a high compression ratio over 200:1.

• Economic and Environmental Geology
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• v.55 no.5
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• pp.551-561
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• 2022

Geophysical exploration methods are very useful for generating high-resolution images of underground structures, and such methods can be applied to investigation of buried cultural properties and for determining their exact locations. In this study, image feature extraction and image segmentation methods were applied to automatically distinguish the structures of buried relics from the high-resolution ground-penetrating radar (GPR) images obtained at the center of Silla Kingdom, Gyeongju, South Korea. The major purpose for image feature extraction analyses is identifying the circular features from building remains and the linear features from ancient roads and fences. Feature extraction is implemented by applying the Canny edge detection and Hough transform algorithms. We applied the Hough transforms to the edge image resulted from the Canny algorithm in order to determine the locations the target features. However, the Hough transform requires different parameter settings for each survey sector. As for image segmentation, we applied the connected element labeling algorithm and object-based image analysis using Orfeo Toolbox (OTB) in QGIS. The connected components labeled image shows the signals associated with the target buried relics are effectively connected and labeled. However, we often find multiple labels are assigned to a single structure on the given GPR data. Object-based image analysis was conducted by using a Large-Scale Mean-Shift (LSMS) image segmentation. In this analysis, a vector layer containing pixel values for each segmented polygon was estimated first and then used to build a train-validation dataset by assigning the polygons to one class associated with the buried relics and another class for the background field. With the Random Forest Classifier, we find that the polygons on the LSMS image segmentation layer can be successfully classified into the polygons of the buried relics and those of the background. Thus, we propose that these automatic classification methods applied to the GPR images of buried cultural heritage in this study can be useful to obtain consistent analyses results for planning excavation processes.