• Journal of Advanced Navigation Technology
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• v.24 no.6
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• pp.485-490
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• 2020

Recently, amid active research on domestic shipbuilding industry and IT convergence technology, with the development of satellite detection technology for ship safety operation, ships monitored the movement of ships with the mandatory long-range identification & tracking of vessels and automatic identification system. It is possible to help safe navigation, but it is necessary to develop safety device that alert the marine officer who rely on radar to correct conditions in case of weightlessness. Therefore, an ocean fog alarm system was developed to detect and inform using photo sensors. The fabricated ocean fog detect and alarm system consists of a small, low-power optical sensor transceiver and data sensing processing module. Through experiment, it is confirmed that the fabricated ocean fog detect and alarm system measure the corresponding concentration of ocean fog for fogless circumstance and fogbound circumstance, respectively. Furthermore, the fabricated system can control RPM of ship engine according to the concentration of ocean fog, and consequently, the fabricated system can be applied to assistant device for ship safety operation.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.7
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• pp.685-691
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• 2020

In this study, an algorithm that recognizes numbers from 0 to 9 was developed using the data obtained after tracking hand movements using the echo signal of a millimeter-wave radar sensor at 77 GHz. The echo signals obtained from the radar sensor by detecting the motion of a hand gesture revealed a cluster of irregular dots due to the difference in scattering cross-sectional area. A valid center point was obtained from them by applying a K-Means algorithm using 3D coordinate values. In addition, the obtained center points were connected to produce a numeric image. The recognition rate was compared by inputting the obtained image and an image similar to human handwriting by applying the smoothing technique to a CNN (Convolutional Neural Network) model trained with MNIST (Modified National Institute of Standards and Technology database). The experiment was conducted in two ways. First, in the recognition experiments using images with and without smoothing, average recognition rates of 77.0% and 81.0% were obtained, respectively. In the experiment of the CNN model with augmentation of learning data, a recognition rate of 97.5% and 99.0% on average was obtained in the recognition experiment using the image with and without smoothing technique, respectively. This study can be applied to various non-contact recognition technologies using radar sensors.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.2
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• pp.117-124
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• 2018

This paper describes the localization development of an axial fan for KM-SAM multi-function radar. The multi-function radar, which is constantly affected by the external environment, is a key instrument for detecting and tracking low and medium altitude threat targets. Operating this equipment smoothly requires a fan for controlling the internal temperature and humidity. Presently, all such fans are imported. To solve these problems, localization development research was proposed. The development of localization includes analysis of requirements through review of related technical reports such as original equipment and system equipment specification, prototype design, and verification of design requirement through performance test and environmental test. The study results are described. The blower consisted of an axial fan with guide vanes and the motor was designed to generate a maximum airflow of 970 CFM and a wind pressure of 4.8 IWG. Six prototypes were manufactured for performance evaluation. In addition, for reliable data acquisition, AC power supply, fan performance tester and data acquisition equipment were designed and tested. All prototypes were verified as having design requirements equal to or better than those of imports.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.2
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• pp.27-39
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• 2015

As a radar based air surveillance hits the limit along with the growing air traffic needs, a new air surveillance technology called ADS-B has emerged. ADS-B provides more accurate position information with a shorter interval, and aircraft equipped with ADS-B transponders can check each other's location. However not all aircraft are equipped with ADS-B transponders, and aircraft with different ADS-B data links cannot check each other's location. To address these problems a TIS-B service, which broadcasts information that a radar is tracking, and an ADS-R service, which cross-broadcasts information of different ADS-B data links, have been emerged. In this paper, we design and implement a centralized TIS-B server for broadcasting air traffic situation which is capable of providing a TIS-B service and an ADS-R service at the same time. The implemented TIS-B server has been verified with a configured ADS-B ground system, by receiving ADS-B surveillance data and radar surveillance data followed by generating surveillance data for providing a TIS-B service and an ADS-R service and simulating broadcast of those generated surveillance data.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.12
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• pp.2511-2517
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• 2009

Recently, a FMCW radar is used for the various purposes in the short range detection and tracking of targets. The main advantages of a FMCWradar are the comparative simplicity of implementation and the low peak power transmission characterizing the very low probability of signal interception. Since it uses the frequency modulated continuous wave for transmission and demodulation, the received beat frequency represents the range and Doppler information of targets. Detection and extraction of useful information from targets are performed in this beat frequency domain. Therefore, the resolution and accuracy in the estimation of a beat spectrum are very important. However, using the conventional FFT estimation method, the high resolution spectrum estimation with a low sidelobe level is not possible if the acquisition time is very short in receiving target echoes. This kind of problems deteriorates the detection performance of adjacent targets having the large magnitude differences in return echoes and also degrades the reliability of the extracted information. Therefore, in this paper, the model parameter estimation methods such as autoregressive and eigenvector spectrum estimation are applied to mitigate these problems. Also, simulation results are compared and analyzed for further improvement.

• Korean Journal of Remote Sensing
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• v.30 no.1
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• pp.83-107
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• 2014

This study presents spatial characteristics of cloud using satellite image in the extreme heavy snowfall of the Yeongdong region. 3 extreme heavy snowfall events in the Yeongdong region during the recent 12 years (2001 ~ 2012) are selected for which the fresh snow cover exceed 50 cm/day. Spatial characteristics (minimum brightness temperature; Tmin, cloud size, center of cloud-cell) of cloud are analyzed by tracking main cloud-cell related with these events. These characteristics are compared with radar precipitation in the Yeongdong region to investigate relationship between cloud and precipitation. The results are summarized as follows, selected extreme heavy snowfall events are associated with the isolated, well-developed, and small-scale convective cloud which is developing over the Yeongdong region or moving from over East Korea Bay to the Yeongdong region. During the period of main precipitation, cloud-cell Tmin is low ($-40{\sim}-50^{\circ}C$) and cloud area is small (17,000 ~ 40,000 $km^2$). Precipitation area (${\geq}$ 0.5 mm/hr) from radar also shows small and isolated shape (4,000 ~ 8,000 $km^2$). The locations of the cloud and precipitation are similar, but in there centers are located closely to the coast of the Yeongdong region. In all events the extreme heavy snowfall occur in the period a developed cloud-cell was moving into the coastal waters of the Yeongdong. However, it was found that developing stage of cloud and precipitation are not well matched each other in one of 3 events. Water vapor image shows that cloud-cell is developed on the northern edge of the dry(dark) region. Therefore, at the result analyzed from cloud and precipitation, selected extreme heavy snowfall events are associated with small-scale secondary cyclone or vortex, not explosive polar low. Detection and tracking small-scale cloud-cell in the real-time forecasting of the Yeongdong extreme heavy snowfall is important.

• Journal of the Korean earth science society
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• v.39 no.4
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• pp.305-316
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• 2018

Satellite-derived sea surface winds (SSWs) and atmospheric motion vectors (AMVs) over the global ocean, particularly including the areas in and around tropical cyclones (TCs), have been provided in a real-time and continuous manner. More and better information is now derived from technologically improved multiple satellite missions and wind retrieving techniques. The status and prospects of key SSW products retrieved from scatterometers, passive microwave radiometers, synthetic aperture radar, and altimeters as well as AMVs derived by tracking features from multiple geostationary satellites are reviewed here. The quality and error characteristics, limitations, and challenges of satellite wind observations described in the literature, which need to be carefully considered to apply the observations for both operational and scientific uses, i.e., assimilation in numerical weather forecasting, are also described. Additionally, on-going efforts toward merging them, particularly for monitoring three-dimensional TC wind fields in a real-time and continuous manner and for providing global profiles of high-quality wind observations with the new mission are introduced. Future research is recommended to develop plans for providing more and better SSW and AMV products in a real-time and continuous manner from existing and new missions.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.34 no.5
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• pp.93-100
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• 2006

This paper presents a multi-sensor data simulator and a data fusion algorithm for tracking high dynamic flight target from Radar and Telemetry System. The designed simulator generates time-asynchronous multiple sensor data with different data rates and communication delays. Measurement noises are incorporated by using realistic sensor models. The proposed fusion algorithm is designed by a 21st order distributed Kalman Filter which is based on the PVA model with sensor bias states. A fault detection and correction logics are included in the algorithm for bad data and sensor faults. The designed algorithm is verified by using both simulation data and actual real data.

• Proceedings of the KSRS Conference
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• v.1
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• pp.126-129
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• 2006

The marine environment is under considerable threat from intentional or accidental oil spills, ballast water discharged, dredging and infilling for coastal development, and uncontrolled sewage and industrial wastewater discharges. Monitoring spills and illegal oil discharges is an important component in ensuring compliance with marine protection legislation and general protection of the coastal environments. For the monitoring task an image processing system is needed that can efficiently perform the detection and the tracking of oil spills and in this direction a significant amount of research work has taken place mainly with the use of radar (SAR) remote sensing data. In this paper the level set image segmentation technique was tested for the detection of oil spills. Level set allow the evolving curve to change topology (break and merge) and therefore boundaries of particularly intricate shapes can be extracted. Experimental results demonstrated that the level set segmentation can be used for the efficient detection and monitoring of oil spills, since the method coped with abrupt shape’s deformations and splits.

• Journal of Advanced Navigation Technology
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• v.18 no.4
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• pp.268-277
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• 2014

It is very important to correlate flight plan for safe and prompt ATC(air traffic control) operation. In this paper, we design CWP(controller working position) MRT(multi radar tracking) processing module to achieve improvement of overall ATC automation system's performance by minimizing network traffic overload when correlating MRT with flight plan. This implemented module can guarantee efficiency and safety of ATC automation system by applying distributed correlated manner, and reduce network usage by using encoded flight plan correlated MRT data format. We found that this module has 8.54~12.11% lower network usage and 8.37~11.27% higher network traffic fairness than the module using standalone manner.