• International journal of advanced smart convergence
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• v.10 no.4
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• pp.263-272
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• 2021

At a time when securing driving safety is the most important in the development and commercialization of autonomous vehicles, AI and big data-based algorithms are being studied to enhance and optimize the recognition and detection performance of various static and dynamic vehicles. However, there are many research cases to recognize it as the same vehicle by utilizing the unique advantages of radar and cameras, but they do not use deep learning image processing technology or detect only short distances as the same target due to radar performance problems. Radars can recognize vehicles without errors in situations such as night and fog, but it is not accurate even if the type of object is determined through RCS values, so accurate classification of the object through images such as cameras is required. Therefore, we propose a fusion-based vehicle recognition method that configures data sets that can be collected by radar device and camera device, calculates errors in the data sets, and recognizes them as the same target.

• Journal of Multimedia Information System
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• v.5 no.4
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• pp.245-256
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• 2018

This study estimated rainfall information more effectively by image signals through the information system of weather radar. Based on this, we suggest the way to estimate quantitative precipitation utilizing overlapped observation area of radars. We used the overlapped observation range of ground hyetometer observation network and radar observation network which are dense in our country. We chose the southern coast where precipitation entered from seaside is quite frequent and used Sungsan radar installed in Jeju island and Gudoksan radar installed in the southern coast area. We used the rainy season data generated in 2010 as the precipitation data. As a result, we found a reflectivity bias between two radar located in different area and developed the new quantitative precipitation estimation method using the bias. Estimated radar rainfall from this method showed the apt radar rainfall estimate than the other results from conventional method at overall rainfall field.

• Journal of electromagnetic engineering and science
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• v.19 no.1
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• pp.13-19
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• 2019

This paper proposes a systematic method for estimating detection performances of a frequency-modulated continuous wave radar using electromagnetic simulations. The proposed systematic method includes a radar system simulator that can obtain range-Doppler images using the electromagnetic (EM) simulations in conjunction with a test setup employed for performance evaluation of multiple targets at different velocities in a traffic environment. This method is then applied for optimizing the half-power beamwidths of the antenna array using an evaluation metric defined to improve the detection strengths for the multiple targets. The optimized antenna has vertical and horizontal half-power beam widths of $10^{\circ}$ and $60^{\circ}$, respectively. The results confirm that that the proposed systematic method is suitable to improve the radar detection performance with the enhanced radar-Doppler images.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.30 no.1
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• pp.88-94
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• 2019

A leakage canceller and adaptive algorithm for FMCW Radar is presented. Because a strong leakage signal causes various problems in the transceiver and digital processor, specific FMCW radars are in need of a leakage canceller. The leakage canceller has an adaptive structure and the algorithm calculates the prediction vector and learns the adaptive coefficient simultaneously. The proposed algorithm an improvement of 10 dB in the cancellation performance.

• IEMEK Journal of Embedded Systems and Applications
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• v.14 no.1
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• pp.11-18
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• 2019

In this paper, we consider interferences from other automobile pulse radars using same frequency spectrum. In order to eliminate the interference, we propose the PN code modulation method. This method uses the cross-correlation between PN codes with different seed. The ROC performance is used for comparing the proposed detector to conventional method. And the proposed detector can decide the present or absent of targets and measure the range of the targets by using memory buffer of range gate. Especially, we use false alarm probability for all range gates. That is the false alarm if in any one range gate the false alarm occurs. From the simulation result, we can see that the proposed detector with using PN code is not influenced by interferences.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.300-302
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• 2019

The mast, which is the highest structure in warships, as well as merchant ships, is mainly equipped with radars and navigation lights. Especially, due to the nature of the naval vessels that operate many communication equipment, various kinds of antennas such as communication antennas and TACAN for aircraft guiding are installed in the naval mast. In addition to the complex structure of the mast itself, the installed antenna is a factor that greatly increases the RCS. Therefore, the mast technology for reducing the RCS is being developed and applied in the United States and Europe.

• Journal of Auto-vehicle Safety Association
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• v.12 no.4
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• pp.7-12
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• 2020

Recently, automobile industries have developed ADAS, smart cars, connected cars, automated driving systems, which use a variety of sensor systems - ultrasonics, cameras, lidars and radars - and communication systems. It is necessary to examine the electromagnetic immunity of vehicles equipped with the sensor systems due to the fact that the normal operation of those systems is very important to the safety of the vehicles. The electromagnetic immunity tests are carried out in an electromagnetic semi anechoic chamber, which is cut off from the outside. It is difficult to create test environments in which the camera sensor systems of vehicles work properly in the test chamber. In this study, test jigs were designed and tested and as a result they are shown to be effective to create test environments for electromagnetic immunity tests of vehicles equipped with camera sensors. We also proposed additional safety standards for immunity tests of vehicles with camera systems that currently do not exist.

• Journal of Sensor Science and Technology
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• v.31 no.1
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• pp.36-40
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• 2022

High-power devices, such as LEDs and radars, inevitably generate a large amount of heat, which is the main cause of shortening lifespan, deterioration in performance, and failure of electronic devices. The embedded IC process can be a solution; however, when applied to large-area substrates (larger than 8 in), there is a limit owing to the difficulty in the process after wafer thinning. In this study, an 8-in wafer-level high-power electronic package based on the embedded IC process was implemented with temporary bonding and debonding technology using double-sided thermal release tape. Good heat-dissipation characteristics were demonstrated both theoretically and experimentally. These findings will advance the commercialization of high-power electronic packaging.

• IEMEK Journal of Embedded Systems and Applications
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• v.17 no.3
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• pp.139-148
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• 2022

In this paper, we implement a distributed FMCW MIMO radar system to obtain Micro Doppler signatures of target motions. In addition, we also develop federated learning based motion recognition algorithm based on the Micro-Doppler radar signature collected by the implemented FMCW MIMO radar system. Through the experiment, we have verified that the proposed federated learning based algorithm can improve the motion recognition accuracy up to 90%.

• IEMEK Journal of Embedded Systems and Applications
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• v.19 no.1
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• pp.39-46
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• 2024

In this paper, we propose an efficient method for estimating the number of people and their locations using multiple IR-UWB radar sensors. Using three IR-UWB radar sensors in the indoor space, the measured signal from the target is processed to remove the clutter using rejection methods. Then, to further remove the clutter and to determine the presence of the human, the time-frequency image representing the micro-Doppler is obtained and classified by a convolutional neural network. Finally, the system finds the number of human objects and estimates each position in a two-dimensional space. In experiments using the measured data, the system successfully estimated the location and number of individuals with a high accuracy ≈ 88.68 %.