• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.62 no.12
• /
• pp.1813-1819
• /
• 2013

Existing level crossing obstacle detecting system was installed using a laser beam. Level crossing obstacle detecting system using a laser beam that has been a problem in relation to safety and maintainability failure according to weather conditions. We proposed laser radar level crossing obstacle detecting system as a way to overcome problem, and we developed an algorithm for this. Level crossing obstacle detecting system using a laser radar sensor algorithm is robust to external environment and a shadow zone does not exist. Sensor part of the laser radar level crossing obstacle detecting system of these is made up by the image processing unit and laser radar sensor, it operations by receiving train entering information from the control unit. In this paper, we proposed a detecting algorithm with calculation of the size of the laser radar sensor. Based on this, we were performance test on the basis of the scenario by making a prototype. In the future, laser radar level crossing obstacle detecting system to ensure the safety and reliability through the field test.

• Journal of the Korean Institute of Navigation
• /
• v.24 no.5
• /
• pp.435-441
• /
• 2000

This paper deals with the development of RACOM(Radar Signal Detecting ＆ Processing Computer). RACOM is a radar display system specially designed for radar scan conversion, signal processing and PCI radar image display. RACOM contains two components； i )RSP(Radar Signal Processor) board which is a PCI based board for receiving video, trigger, heading & bearing signals from radar scanner ＆ tranceiver units and processing these signals to generate high resolution radar image, and ⅱ）Applications which perform ordinary radar display functions such as EBL, VRM and so on. Since RACOM is designed to meet a wide variety of specifications(type of output signal from tranceiver unit), to record radar images and to distribute those images in real time to everywhere in a networked environment, it can be applicable to AIS(Automatic Identification System) and VDR(Voyage Data Recorder).

• Proceedings of the Korea Concrete Institute Conference
• /
• 2005.11a
• /
• pp.229-232
• /
• 2005

More than effectively judging the existence of voids behind concrete tunnel linings or under concrete pavements, this research aims to develop the analysis algorithm of radar capable of estimation of the shape of specific voids. To detect or estimate void shapes in non-reinforced concrete, the simulation analysis model of transmission and reflection wave of electromagnetic radar is used. This radar simulation model is carried out with various void shapes. As the results, a proposed method in this study has a possibility of detecting or estimating void shapes with good accuracy.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.39C no.3
• /
• pp.307-315
• /
• 2014

Existing level crossing obstruction detecting system occurs section of not detecting an obstruction by line detecting. Due to installation of decentralized equipment, it has become a problem in terms of safety and maintenance costs. accordingly, We have developed level crossing obstruction detecting system using laser radar sensor in order to solve these problems. In this paper, Describe results of functional test for the developed level crossing obstruction detecting system. functional tests are normal operation test(control unit and sensor unit) and test to display the fault information in event of a failure(control unit and sensor unit). It was confirmed that it works properly all according to functional test of level crossing obstruction detecting system using laser radar sensor.

• Journal of KIISE
• /
• v.43 no.8
• /
• pp.848-856
• /
• 2016

Seeking and recognizing maritime targets are very important tasks for maritime safety. While searching for maritime targets using radar is possible, recognition is conducted without automatic identification system, radio communicator or visibility. If this recognition is not feasible, radar operator must tediously recognize maritime targets using movement features on radar base on know-how and experience. In this paper, to support the radar operator's mission of continuous observation, we propose an algorithm for automatic recognition of an unknown ship using movement features on radar and a method of detecting potential ship related accidents. We extract features from contact range, course and speed of four types of vessels and evaluate the recognition accuracy using SVM and suggest a method of detecting potential ship related accidents through the algorithm. Experimentally, the resulting recognition accuracy is found to be more than 90% and presents the possibility of detecting potential ship related accidents through the algorithm using information of MV Sewol. This method is an effective way to support operator's know-how and experience in various circumstances and assist in detecting potential ship related accidents.

• Atmosphere
• /
• v.30 no.4
• /
• pp.347-360
• /
• 2020

The automatic algorithm optimized for the Korean Peninsula was developed to detect and track the center of typhoon based on a geometrical method using high-resolution retrieved WISSDOM (WInd Syntheses System using DOppler Measurements) wind and reflectivity data. This algorithm analyzes the center of typhoon by detecting the geometric circular structure of the typhoon's eye in radar reflectivity and vorticity 2D field data. For optimizing the algorithm, the main factors of the algorithm were selected and the optimal thresholds were determined through sensitivity experiments for each factor. The center of typhoon was detected for 5 typhoon cases that approached or landed on Korean Peninsula. The performance was verified by comparing and analyzing from the best track of Korea Meteorological Administration (KMA). The detection rate for vorticity use was 15% higher on average than that for reflectivity use. The detection rate for vorticity use was up to 90% for DIANMU case in 2010. The difference between the detected locations and best tracks of KMA was 0.2° on average when using reflectivity and vorticity. After the optimization, the detection rate was improved overall, especially the detection rate more increased when using reflectivity than using vorticity. And the difference of location was reduced to 0.18° on average, increasing the accuracy.

• Journal of Ocean Engineering and Technology
• /
• v.24 no.2
• /
• pp.53-56
• /
• 2010

Oil spills and red tide can be very damaging to the environment and fishery farming. These catastrophic accidents must be detected as quickly as possible. In this paper, we report the results of applying the wavelet transform to SAR or marine radar images for the detection of the boundaries of an oil spill or red tide. The application of the wavelet transform to these phenomena looks quite promising in detecting the boundaries of oil spills and red tide areas.

• Proceedings of the Korea Concrete Institute Conference
• /
• 2006.05a
• /
• pp.602-605
• /
• 2006

Locating reinforcing bars, in particular to know their accurate depths and horizontal distances, is very important in radar inspection of concrete structures. By the way, it is not easy for an accurate depth and horizontal distance estimation of reinforcing bars in concrete structures by the radar test. This problem can be solved by synthetic aperture radar method. To improve the vertical and horizontal resolution of reinforcing bars in concrete, synthetic aperture radar method was examined in this study.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
• /
• v.27 no.2
• /
• pp.131-137
• /
• 2016

In this paper, a feasibility on a ground-penetrating radar for detecting subsurface cavities near buried pipes has been investigated. The experimental setup was implemented by employing an impulse ground-penetrating radar system, a xy Cartesian coordinate robot, an underground material filled tank, a metal pipe and a simulated cavity model. In particular, the simulated cavity model was constructed by packing Styrofoam chips and balls, which have both similar electrical properties to an air-filled cavity and a solid shape. Through typical three experiments, B-scan data of the radar have been acquired and displayed as 2-D gray-scale images. According to the comparison of B-scan images, we show that the subsurface cavities near the buried pipes can be detected by using the radar survey.

• IEMEK Journal of Embedded Systems and Applications
• /
• v.13 no.6
• /
• pp.289-296
• /
• 2018

Drone detection in FMCW radar system needs complex techniques because a drone beat frequency is highly dynamic and unpredictable. Therefore, the current static signal processing algorithms cannot show appropriate detection accuracy. With dynamic signal fluctuation and environmental clutters, it can fail to detect a drone or make false detection. It affects to the radar system integrity and safety. Constant false alarm rate (CFAR), one of famous static signal process algorithm is effective for static environment. But for drone detection, it shows low detection accuracy. In this paper, we suggest neural network based FMCW radar system for detecting a drone. We use recurrent neural network (RNN) because it is the effective neural network for signal processing. In our FMCW radar system, one transmitter emits FMCW signal and four-way fixed receivers detect reflected drone beat frequency. The coordinate of the drone can be calculated with four receivers information by triangulation. Therefore, RNN only learns and inferences reflected drone beat frequency. It helps higher learning and detection accuracy. With several drone flight experiments, RNN shows false detection rate and detection accuracy as 21.1% and 96.4%, respectively.