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

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.29 no.8
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• pp.640-647
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• 2018

This study analyzes the tracking accuracy(tracking errors) of fighter radar. Measurement error, detection failure, and radar cross section(RCS) fluctuation in radar measurements degrade the measurement quality and hence affect the tracking accuracy. Therefore, these radar measurement characteristics need to be considered when analyzing the tracking accuracy. In this paper, a method for analyzing the tracking accuracy is proposed; this method considers the detection error, detection probability, and RCS fluctuation. Results from experiments conducted with the proposed method show that the detection probability and RCS fluctuation affect tracking accuracy.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.1
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• pp.123-129
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• 2014

This paper presents an altitude detection accuracy for long range and multifunction radar. The accuracy is difficult to estimate because it is affected by an time varying atmosphere refractivity. We analyze altitude accuracy with a raytracing simulator with atmosphere refractivity. An altitude error is simulated with measured and modeled refractivity, and the modeled refractivity is used for compensate an altitude accuracy. As a result, the error is modeled with normal distribution function, and analyzed.

• Korean Journal of Remote Sensing
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• v.33 no.1
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• pp.61-67
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• 2017

The detection of oil spills using radar image has been studied extensively. However, most of the proposed techniques have been focused on improving detection accuracy through the advancement of algorithms. In this study, research has been conducted to improve the accuracy of oil spill detection by improving the quality of radar images, which are used as input data to detect oil spills. Thresholding algorithms were used to measure the image improvement both before and after processing. The overall accuracy increased by approximately 16%, the producer accuracy increased by 40%, and the user accuracy increased by 1.5%. The kappa coefficient also increased significantly, from 0.48 to 0.92.

• Korean Journal of Remote Sensing
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• v.33 no.1
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• pp.89-95
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• 2017

Ship detection in synthetic aperture radar(SAR)imagery has long been an active research topic and has many applications. In this paper,we propose an efficient method for detecting ships from SAR imagery using filtering. This method exploits ship masking using a median filter that considers maximum ship sizes and detects ships from the reference image, to which a Non-Local means (NL-means) filter is applied for speckle de-noising and a differential image created from the difference between the reference image and the median filtered image. As the pixels of the ship in the SAR imagery have sufficiently higher values than the surrounding sea, the ship detection process is composed primarily of filtering based on this characteristic. The performance test for this method is validated using KOMPSAT-5 (Korea Multi-Purpose Satellite-5) SAR imagery. According to the accuracy assessment, the overall accuracy of the region that does not include land is 76.79%, and user accuracy is 71.31%. It is demonstrated that the proposed detection method is suitable to detect ships in SAR imagery and enables us to detect ships more easily and efficiently.

• Journal of Sensor Science and Technology
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• v.23 no.3
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• pp.149-157
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• 2014

This paper considers the ability of counting and positioning multi-targets by using a mobile UWB radar device. After a background subtraction process, distinguishing between clutters and human body signals, the position of targets will be computed using weighted Gaussian mixture methods. While computer vision offers many advantages, it has limited performance in poor visibility conditions (e.g., at night, haze, fog or smoke). UWB radar can provide a complementary technology for detecting and tracking humans, particularly in poor visibility or through-wall conditions. As we know, for 2D measurement, one method is the use of at least two receiver antennas. Another method is the use of one mobile radar receiver. This paper tried to investigate the position detection of the stationary human body using the movement of one UWB radar module.

• Transactions of the Korean Society of Automotive Engineers
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• v.22 no.7
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• pp.31-39
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• 2014

Recently, as Intelligent Transportation System (ITS) and self-driving system become influential in the ground transportation system, automotive radar systems have been actively studied among the various radar systems to implement the vehicle collision detection system and distance measurement system between vehicles. Most of the automotive radars are Frequency Modulated Continuous Wave (FMCW) radar type which can calculate distance and velocity of target by estimating the frequency difference between the transmitted signal and received signal. Therefore, accurate frequency estimation is very important in the FMCW radar system. For this reason, to improve the measurement accuracy of the FMCW radar, Reverse Directional FRI (RD-FRI) Super-Resolution technique which has high frequency estimation accuracy is applied to the FMCW radar system. The feasibility of the proposed technique is evaluated with simulation results and compared with FFT and conventional Super-Resolution techniques. The simulation results show that the proposed technique estimates the frequency with high accuracy and the distance with centimeter accuracy.

• Atmosphere
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• v.30 no.4
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• pp.347-360
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• 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 the Korea Institute of Military Science and Technology
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• v.13 no.6
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• pp.1006-1012
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• 2010

For the autonomous navigation of an unmanned ground vehicle in the rough terrain and combat, the dust environment should necessarily be overcome. Therefore, we propose a robust obstacle detection methodology using laser range sensor and radar. Laser range sensor has a good angle and distance accuracy, however, it has a weakness in the dust environment. On the other hand, radar has not better the angle and distance accuracy than laser range sensor, it has a robustness in the dust environment. Using these characteristics of laser range sensor and radar, we use laser range sensor as a main sensor for normal times and radar as a assist sensor for the dust environment. For fusion of laser range sensor and radar information, the angle and distance data of the laser range sensor and radar are separately transformed to the angle and distance data of virtual range sensor which is located in the center of the vehicle. Through distance comparison of laser range sensor and radar in the same angle, the distance data of a fused virtual range sensor are changed to the distance data of the laser range sensor, if the distance of laser range sensor and radar are similar. In the other case, the distance data of the fused virtual range sensor are changed to the distance data of the radar. The suggested methodology is verified by real experiment.

• Journal of Navigation and Port Research
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• v.44 no.2
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• pp.110-118
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• 2020

With the expansion of the shipping and port logistics industry in the 21st century, the traffic density is continuously increased because of the increase in volumes of world sea freight and fleets, as well as the increase in the causes of potential marine accidents, such as ship collisions and stranding. Accordingly, the International Maritime Organization (IMO) has requested that the installation and operation of VTS should be applied in areas with high risk of marine traffic, and the request should be included as one of the Safety of Life at Sea (SOLAS) regulations. In this paper, the fundamental requirements of the radar system for vessel traffic services were analyzed and the analyzing factors were based on the IALA guideline.s This paper also includes results for the requirement and recommendation analysis on detection distance, target separation, and the target position accuracy of X-band radar. Also, to check if it satisfies the requirement of detection distance, range and azimuth separation of small point targets, and target position accuracy from the IALA guidelines, the test was conducted through the radar image acquired at the VTS center, and hence, the validity of the technical performance requirements was confirmed.