• 제목/요약/키워드: radar image

검색결과 560건 처리시간 0.027초

부산 용호만에서 선박용 X-band 레이더에 의한 쇄파의 원격 모니터링 (Remote monitoring of the breaking ocean waves by a marine X-band radar in Yongho Man, Busan)

  • 이대재
    • 수산해양기술연구
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    • 제48권3호
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    • pp.227-234
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    • 2012
  • This paper describes the remote monitoring of breaking ocean waves generated by Typhoon Nabi, whose name means butterfly in Korean, using a marine X-band radar in the Yongho Man, Busan, Korea. The basic purpose of this study is to investigate the dynamic behavior and to estimate the periods of breaking waves across the surf zone from radar image sequences. In these experiments, the land-based radar system imaged the inshore zone of three miles from the coastline to a isobath of 30 meters. The wave period and the dominant wave direction for breaking ocean waves extracted directly from radar image sequences were 157.4 meters and 298 degrees, respectively. However, the result calculated quantitatively by the continuous wavelet transform (CWT) showed that the period of breaking waves was 154.3 meters. The average difference in breaking wave periods between the value extracted by using EBRL (electronic bearing and range line) of radar and the calculated value by CWT was 3.1 meters, showing that the CWT method is also accurate. These results suggest that a marine X-band radar system is a viable method of monitoring the breaking ocean waves.

일반화 Hough변환을 응용한 콘크리트 레이더 화상 내 실제 철근위치의 검출 해석 (Locating Reinforcing Bars in Concrete Structures Using Generalized Hough Transform of Radar Image)

  • 박석균
    • 콘크리트학회논문집
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    • 제12권1호
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    • pp.23-31
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    • 2000
  • Locating reinforcing bars, in particular to know their accurate depths, is very important in radar inspection of concrete structures. By the way, an accurate depth estimation of reinforcing bars in concrete structures by the radar is not easy because the microwave propagation velocity in test area is generally unknown. This problem can be solved by generalized Hough transformation technique. Using this technique, the microwave propagation velocity in test area can be detected from the radar image, which appear as hyperbolas conveying the velocity information in their shape. A developed speed-up technique for the computation of the Generalized Hough transformation is also investigated in this study. As a result, although it becomes difficult to locate reinforcing bars when multiple parallel bars lying too close together, there is a possibility of detecting accurate depths of reinforcing bars in test area by the proposed method

Target-to-Clutter Ratio Enhancement of Images in Through-the-Wall Radar Using a Radiation Pattern-Based Delayed-Sum Algorithm

  • Lim, Youngjoon;Nam, Sangwook
    • Journal of electromagnetic engineering and science
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    • 제14권4호
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    • pp.405-410
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    • 2014
  • In this paper, we compare the quality of images reconstructed by a conventional delayed-sum (DS) algorithm and radiation pattern-based DS algorithm. In order to evaluate the quality of images, we apply the target-to-clutter ratio (TCR), which is commonly used in synthetic aperture radar (SAR) image assessment. The radiation pattern-based DS algorithm enhances the TCR of the image by focusing the target signals and preventing contamination of the radar scene. We first consider synthetic data obtained through GprMax2D/3D, a finite-difference time-domain (FDTD) forward solver. Experimental data of a 2-GHz bandwidth stepped-frequency signal are collected using a vector network analyzer (VNA) in an anechoic chamber setup. The radiation pattern-based DS algorithm shows a 6.7-dB higher TCR compared to the conventional DS algorithm.

선별적인 임계값 선택을 이용한 준지도 학습의 SAR 분류 기술 (Semi-Supervised SAR Image Classification via Adaptive Threshold Selection)

  • 도재준;유민정;이재석;문효이;김선옥
    • 한국군사과학기술학회지
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    • 제27권3호
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    • pp.319-328
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    • 2024
  • Semi-supervised learning is a good way to train a classification model using a small number of labeled and large number of unlabeled data. We applied semi-supervised learning to a synthetic aperture radar(SAR) image classification model with a limited number of datasets that are difficult to create. To address the previous difficulties, semi-supervised learning uses a model trained with a small amount of labeled data to generate and learn pseudo labels. Besides, a lot of number of papers use a single fixed threshold to create pseudo labels. In this paper, we present a semi-supervised synthetic aperture radar(SAR) image classification method that applies different thresholds for each class instead of all classes sharing a fixed threshold to improve SAR classification performance with a small number of labeled datasets.

강우의 불확실성에 관한 강우레이더 영상 품질관리 알고리즘 (Quality Control Algorithm of Rainfall Radar Image for Uncertainty of Rainfall)

  • 최정호;유철상;임상훈;한명선;이배규
    • 한국멀티미디어학회논문지
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    • 제20권12호
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    • pp.1874-1889
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    • 2017
  • The paper aims to analyze structure of I/Q data observed from radar and reliably estimate rainfall through quality control of I/Q data that can quantify uncertainty of I/Q data occurring due to resultant errors. Radar rainfall data have strong uncertainty due to various factors influencing quality. In order to reduce this uncertainty, previously enumerated errors in quality need to be eliminated. However, errors cannot be completely eliminated in some cases as seen in random errors, so uncertainty is necessarily involved in radar rainfall data. Multi-Lag Method, one of I/Q data quality control methods, was applied to estimate precipitation with regard to I/Q data of rainfall radar in Mt. Sobaek.

ISAR 영상 기반 해상표적 식별을 위한 인공지능 연구 (An Artificial Intelligence Research for Maritime Targets Identification based on ISAR Images)

  • 김기태;임요준
    • 산업경영시스템학회지
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    • 제45권2호
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    • pp.12-19
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    • 2022
  • Artificial intelligence is driving the Fourth Industrial Revolution and is in the spotlight as a general-purpose technology. As the data collection from the battlefield increases rapidly, the need to us artificial intelligence is increasing in the military, but it is still in its early stages. In order to identify maritime targets, Republic of Korea navy acquires images by ISAR(Inverse Synthetic Aperture Radar) of maritime patrol aircraft, and humans make out them. The radar image is displayed by synthesizing signals reflected from the target after radiating radar waves. In addition, day/night and all-weather observations are possible. In this study, an artificial intelligence is used to identify maritime targets based on radar images. Data of radar images of 24 maritime targets in Republic of Korea and North Korea acquired by ISAR were pre-processed, and an artificial intelligence algorithm(ResNet-50) was applied. The accuracy of maritime targets identification showed about 99%. Out of the 81 warship types, 75 types took less than 5 seconds, and 6 types took 15 to 163 seconds.

시간-주파수 영역 해석법을 이용한 레이더 영상 품질 개선에 대한 연구 (Improvement of Radar Images Using Time-Frequency Transform)

  • 정상원;김경태
    • 한국전자파학회논문지
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    • 제21권1호
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    • pp.14-19
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    • 2010
  • 본 논문에서는 흐려진 ISAR(Inverse Synthetic Aperture Radar) 영상의 회전 오차를 보상하기 위해 시간-주파수 영역 해석법을 이용한 회전 이동 보상(rotational motion compensation) 알고리즘을 제시한다. 실제의 비행 환경에서는 표적의 회전이나 가속 등의 움직임으로 인하여 도플러 주파수 천이가 시간에 따라 변하게 되고, 이에 따라 회전 오차(motion error)가 발생한다. 본 알고리즘으로 도플러 주파수 영역 방향으로 흐려진 ISAR 영상을 개선한다. 시뮬레이션 결과, 기동하는 표적에 회전 오차가 있을 경우에 시간-주파수 영역 해석법은 흐려진 레이더 영상의 품질을 개선하는데 효율적임을 알 수 있다.

EGI Velocity Integration Algorithm for SAR Motion Measurement

  • Lee, Soojeong;Park, Woo Jung;Park, Yong-gonjong;Park, Chan Gook;Song, Jong-Hwa;Bae, Chang-Sik
    • Journal of Positioning, Navigation, and Timing
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    • 제8권4호
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    • pp.175-181
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    • 2019
  • This paper suggests a velocity integration algorithm for Synthetic Aperture Radar (SAR) motion measurement to reduce discontinuity of range error. When using position data from Embedded GPS/INS (EGI) to form SAR image, the discontinuity of the data degrades SAR image quality. In this paper, to reduce the discontinuity of EGI position data, EGI velocity integration is suggested which obtains navigation solution by integrating velocity data from EGI. Simulation shows that the method improves SAR image quality by reducing the discontinuity of range error. INS is a similar algorithm to EGI velocity integration in the way that it also obtains navigation solution by integrating velocity measured by IMU. Comparing INS and EGI velocity integration according to grades of IMU and GPS, EGI velocity integration is more suitable for the real system. Through this, EGI velocity integration is suggested, which improves SAR image quality more than existing algorithms.

Evaluation of SAR Image Quality

  • Lee Young-ran;Kim Kwang Young;Kwak Sunghee;Shin Dongseok;Jeong Soo;Kim Kyung-Ok
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2004년도 Proceedings of ISRS 2004
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    • pp.397-400
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    • 2004
  • Synthetic Aperture Radar(SAR) is an active micro­wave instrument that performs high-resolution observation under almost all weather conditions. Although there are many advantages of SAR instrument, many complicated steps are involved in order to generate SAR image products. Many research and algorithms have been proposed to process radar signal and to increase the quality of SAR products. However, it is hard to find research which compare the quality of SAR products generated with different algorithms and processing methods. In our previous research, a SAR processing s/w was developed for a ground station. In addition, quality assessment procedures and their test parameters inside a SAR processor was proposed. The purpose of this paper is to evaluate the quality of SAR images generated from the developed SAR processing s/w. However, If there are no direct measurements such as radar reflector or scattering field measurement values it is difficult to compare SAR images generated with different methods. An alternative procedures and parameters for SAR image quality evaluation are presented and the problems involved in the comparison methods are discussed. Experiments based on real data have been conducted to evaluate and analyze quality of SAR images.

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Probing of Concrete Specimens using Ground Penetration Radar

  • Rhim, HongChul
    • Corrosion Science and Technology
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    • 제3권6호
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    • pp.262-264
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    • 2004
  • Ground Penetrating Radar (GPR) has been used to image inside concrete specimens embedded with steel bars and delamination. An imaging algorithm has been developed to improve measurement output generated from a commercial radar system. For the experiments, laboratory size concrete specimens are made with the dimensions of $1,000mm(W){\times}1,000mm(L){\times}250mm(D)$. The results have shown improved output of the radar measurements compared to commercially available processing methods.