• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.4A
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• pp.440-449
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• 2008

In this paper, we propose a 16-QAM carrier recovery loop which is suitable for the implementation of Inmarsat M4 system receiver. Because the frequency offset of ${\pm}924\;Hz$ on signal bandwidth 33.6 kHz is recommended in Inmarsat M4 system specification, carrier recovery loop having stable operation in the channel environment with large relative frequency offset is required. the carrier recovery loop which adopts only PLL can't be stable in relatively large frequency offset environment. Therefore, we propose a carrier recovery loop which has stable operation in large relative frequency offset environment for Inmarsat M4 system. The proposed carrier recovery loop employed differential filter-based noncoherent UW detector which is robust to frequency offset, CP-AFC for initial frequency offset acquisition using UW signal, and 16-QAM DD-PLL for phase tracking using data signal to overcome large relative frequency offset and achieve stable carrier recovery performance. Simulation results show that the proposed carrier recovery loop has stable operation and satisfactory performance in large relative frequency offset environment for Inmarsat M4 system.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.6
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• pp.1099-1110
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• 2023

The recognition system of autonomous driving and robot navigation performs vision work such as object recognition, tracking, and lane detection after multi-sensor fusion to improve performance. Currently, research on a deep learning model based on the fusion of a camera and a lidar sensor is being actively conducted. However, deep learning models are vulnerable to adversarial attacks through modulation of input data. Attacks on the existing multi-sensor-based autonomous driving recognition system are focused on inducing obstacle detection by lowering the confidence score of the object recognition model.However, there is a limitation that an attack is possible only in the target model. In the case of attacks on the sensor fusion stage, errors in vision work after fusion can be cascaded, and this risk needs to be considered. In addition, an attack on LIDAR's point cloud data, which is difficult to judge visually, makes it difficult to determine whether it is an attack. In this study, image scaling-based camera-lidar We propose an attack method that reduces the accuracy of LCCNet, a fusion model (camera-LiDAR calibration model). The proposed method is to perform a scaling attack on the point of the input lidar. As a result of conducting an attack performance experiment by size with a scaling algorithm, an average of more than 77% of fusion errors were caused.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.3
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• pp.1302-1309
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• 2012

In this paper, we propose applying differential techniques for 2D/3D video conversion to the objects grouped by depth information. One of the problems converting 2D images to 3D images using the technique tracking the motion of pixels is that objects not moving between adjacent frames do not give any depth information. This problem can be solved by applying relative height cue only to the objects which have no moving information between frames, after the process of splitting the background and objects and extracting depth information using motion vectors between objects. Using this technique all the background and object can have their own depth information. This proposed method is used to generate depth map to generate 3D images using DIBR(Depth Image Based Rendering) and verified that the objects which have no movement between frames also had depth information.

• Journal of the Korean Society of Radiology
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• v.12 no.1
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• pp.65-70
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• 2018

Computed tomography system is widely used on various fields because section image of an object can be acquired. During several step to obtain section image, artifacts by many error factors can be added on the image. Ring artifact induced by the CT system is examined in this study. A test phantom of $512{\times}512$ size was constructed numerically, and the ring artifact was investigated by the algebraic reconstruction technique. The computer program was realized using Visual C++ under the fan beam geometry with projections of 720 and detector pixel of 1,280. The generation of ring artifact was verified by applying different detection efficiency on detector pixels. The ring intensity became large as increasing the ring value, and the ring artifacts were strongly emphasized near the center of the reconstructed image. The ring artifact may be eliminated by tracking the position of ring artifact on the reconstructed image and by calibrating the detector pixel.

• Journal of Korea Water Resources Association
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• v.49 no.9
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• pp.749-759
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• 2016

The aim of this study is to apply and to evaluate the radar-based risk prediction algorithm for damage reduction by sudden localized heavy rain in urban areas. The algorithm is combined with three processes such as "detection of cumulonimbus convective cells that can cause a sudden downpour", "automatic tracking of the detected convective cells", and "risk prediction by considering the possibility of sudden downpour". This algorithm was applied to rain events that people were marooned in small urban stream. As the results, the convective cells were detected through this algorithm in advance and it showed that it is possible to determine the risk of the phenomenon of developing into local heavy rain. When use this risk predicted results for flood prevention operation, it is able to secure the evacuation time in small streams and be able to reduce the casualties.

• The Journal of the Convergence on Culture Technology
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• v.9 no.4
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• pp.277-281
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• 2023

Recent aggressive threats by North Korea using small drones have heavily impacted on ROK(Republic of Korea) society and it seems to be agreed that counter-drone systems are required to protect our properties. ROK government has been investigating current counter-drone systems for national important facilities. However, there is no consensus standard to evaluate the systems. This paper is to propose a counter-drone system evaluation framework which is the outcome through RMA(Revolution in Military Affairs) thinking process. The RMA thinking process is currently well-implemented in ROK army to develop future military strategy. The proposed framework has 4 categories - threat analysis of North Korea small drones, convergence of detection, tracking and neutralizing systems, integrated operations and available experts and organization - which have corresponding criteria.

• KIPS Transactions on Computer and Communication Systems
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• v.2 no.1
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• pp.7-14
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• 2013

Presently, there are many different technologies used for position detection. However, as signal-receiving devices operating in different locations must detect the precise position of objects located at long distances, it is essential to know the precise time at which an object's or a user's terminal device sends a signal. For this purpose, the existing time of arrival (ToA) technology is not sufficiently reliable, and the existing time difference of arrival (TDoA) technology is more suitable. If a TDoA-based electric surveillance system and other tracking devices fail to achieve precise time-synchronization between devices with separation distance operation, it is impossible to obtain correct TDoA values from the signals sent by the signal-receiving devices; this failure to obtain the correct values directly affects the location estimation error. For this reason, the technology for achieving precise time synchronization between signal-receiving devices in separation distance operation, among the technologies previously mentioned, is a core technology for detecting TDoA-based locations. In this paper, the accuracy of the proposed time synchronization and the measurement error in the TDoA-based location detection technology is evaluated. The TDoA-based location measurement error is significantly improved when using the proposed method for time-synchronization error reduction.

• Korean Journal of Remote Sensing
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• v.38 no.5_3
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• pp.925-938
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• 2022

Agricultural reservoirs are an important water resource nationwide and vulnerable to abnormal climate effects such as drought caused by climate change. Therefore, it is required enhanced management for appropriate operation. Although water-level tracking is necessary through continuous monitoring, it is challenging to measure and observe on-site due to practical problems. This study presents an objective comparison between multiple AI models for water-body extraction using radar images that have the advantages of wide coverage, and frequent revisit time. The proposed methods in this study used Sentinel-1 Synthetic Aperture Radar (SAR) images, and unlike common methods of water extraction based on optical images, they are suitable for long-term monitoring because they are less affected by the weather conditions. We built four AI models such as Support Vector Machine (SVM), Random Forest (RF), Artificial Neural Network (ANN), and Automated Machine Learning (AutoML) using drone images, sentinel-1 SAR and DSM data. There are total of 22 reservoirs of less than 1 million tons for the study, including small and medium-sized reservoirs with an effective storage capacity of less than 300,000 tons. 45 images from 22 reservoirs were used for model training and verification, and the results show that the AutoML model was 0.01 to 0.03 better in the water Intersection over Union (IoU) than the other three models, with Accuracy=0.92 and mIoU=0.81 in a test. As the result, AutoML performed as well as the classical machine learning methods and it is expected that the applicability of the water-body extraction technique by AutoML to monitor reservoirs automatically.

• Journal of the HCI Society of Korea
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• v.2 no.1
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• pp.57-63
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• 2007

Our research was performed in order to implement a new pointing device for human-computer interactions in a collaborative environments based on Tiled Display system. We mainly focused on tracking the position of an infrared light source and applying our system to various areas. More than simple functionality of mouse clicking and pointing, we developed a device that could be used to help people communicate better with the computer. The strong point of our system is that it could be implemented in any place where a camera can be installed. Due to the fact that this system processes only infrared light, computational overhead for LED recognition was very low. Furthermore, by analyzing user's movement, various actions are expected to be performed with more convenience. This system was tested for presentation and game control.

• Journal of Internet of Things and Convergence
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• v.5 no.1
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• pp.7-11
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• 2019

This study suggests a methodology to track crime suspects or anomalies through CCTV in order to expand the scope of CCTV use as the number of CCTV installations continues to increase nationwide in recent years. For the abnormal behavior classification, we use the existing studies to find out suspected criminals or abnormal actors, use CNN to track objects, and connect the surrounding CCTVs to each other to predict the movement path of objectified objects CCTVs in the vicinity of the path were used to share objects' sample data to track objects and to track objects. Through this research, we will keep track of criminals who can not be traced, contribute to the national security, and continue to study them so that more diverse technologies can be applied to CCTV.