• Korean Journal of Optics and Photonics
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• v.31 no.2
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• pp.59-70
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• 2020

We discuss a modified numerical model based on the Monte Carlo radiative transfer (MCRT) method, i.e., the MCRT matrix method, for the analysis of atmospheric scattering effects in three-dimensional flash LIDAR systems. Based on the MCRT method, the radiative transfer function for a LIDAR signal is constructed in a form of a matrix, which corresponds to the characteristic response. Exploiting the superposition and convolution of the characteristic response matrices under the paraxial approximation, an extended computer simulation model of an overall flash LIDAR system is developed. The MCRT matrix method substantially reduces the number of tracking signals, which may grow excessively in the case of conventional Monte Carlo methods. Consequently, it can readily yield fast acquisition of the signal response under various scattering conditions and LIDAR-system configurations. Using the computational model based on the MCRT matrix method, we carry out numerical simulations of a three-dimensional flash LIDAR system operating under different atmospheric conditions, varying the scattering coefficient in terms of visible distance. We numerically analyze various phenomena caused by scattering effects in this system, such as degradation of the signal-to-noise ratio, glitches, and spatiotemporal spread and time delay of the LIDAR signals. The MCRT matrix method is expected to be very effective in analyzing a variety of LIDAR systems, including flash LIDAR systems for autonomous driving.

• Proceedings of the Korea Multimedia Society Conference
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• 2004.05a
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• pp.69-73
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• 2004

일반적으로 스트림 방식의 DRM(Digital Rights Management)시스템은 한번에 하나의 컨텐츠만을 구매할 수 있다 그러므로 다중 디지털 컨텐츠의 구매 시에 매번의 인증, 지불, 라이센스 획득 단계가 필요하다. 게다가 구매한 모든 컨텐츠의 라이센스 키들의 안전한 저장 공간이 필요함으로 라이센스 키 관리의 어려움이 있다. 따라서 본 논문은 Atallah와 Li[1]의 스마트카드를 이용한 라이센스 키 관리 방식의 문제점을 지적하고, 스트림 방식의 DRM 시스템에서 다중 컨텐츠 구매를 위한 효율적인 다중 라이센스(multi-license) 서비스를 제안한다.

• Journal of IKEEE
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• v.23 no.1
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• pp.44-52
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• 2019

We implement an educational indoor autonomous mobile robot system that integrates LiDAR sensing information with RGB-D camera image information and exploits the integrated information. This system uses the existing sensing method employing a LiDAR with a small number of scan channels to acquire LiDAR sensing information. To remedy the weakness of the existing LiDAR sensing method, we propose the 3D structure recognition technique using depth images from a RGB-D camera and the deep learning based object recognition algorithm and apply the proposed technique to the system.

• Proceedings of the Korean Information Science Society Conference
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• 2004.10a
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• pp.604-606
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• 2004

클라이언트/서버 시스템은 클라이언트가 수행할 수 없거나 곤란한 프로그램을 서버에서 수행하여 클라이언트의 부하를 줄여준다. 하지만 서버의 리소스를 요청하는 클라이언트의 수가 많아지면 이미 많은 리소스를 사용하고 있는 서버에게 리소스를 요청하거나, 리소스를 사용하지 않는 서비스에게는 요청하지 않는 경우가 발생하여 서버에게 너무 많은 부하를 주거나 전혀 부하가 생기지 않을 수 있다. 이에 본 논문에서는 Jini 기반의 Agent Manager를 이용하여 서버와 클라이언트의 정보를 수집한 다음 MAUT와 Maximum-Weight Matching을 이용하여 클라이언트와 서버 간 연결의 전체적인 만족도를 높이는 Jini 기반의 최적의 컴퓨팅 리소스 제안 시스템을 연구하였다.

• Proceedings of the Optical Society of Korea Conference
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• 2003.02a
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• pp.212-213
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• 2003

대기 중에 존재하는 에어로졸은 지구 복사수지에 영향을 줄뿐 만 아니라 기상학적으로 구름의 응결 핵으로 작용하는 것으로 알려져 있다. 그러므로 이에 대한 보다 정확한 물리·화학적 정보를 얻기 위해 많은 연구가들이 측정을 수행하고 있지만, 기존의 측정 시스템은 에어로졸의 시·공간적 변화를 정확하게 측정하기에는 많은 문제점을 가지고 있다. 라이다 시스템을 이러한 문제를 해결하는데 유용한 장비로써 대기중에 존재하는 에어로졸의 광학적 특성(후방산란계수, 편광소멸도, 라이다 비 등)을 보다 정확하게 측정할 수 있는 장비로 알려져 있다. (중략)

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.26 no.3
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• pp.311-320
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• 2008

A LIDAR can rapidly generate 3D points by densely sampling the surfaces of targets using laser pulses, which has been efficiently utilized to reconstruct 3D models of the targets automatically. Due to this advantage, LIDARs are increasingly applied to the fields of Defense and Security, for examples, being employed to intelligently guided missiles and manned/unmanned reconnaissance planes. For the prior verification of the LIDAR applicability, this study aims at generating simulated LIDAR data. Here, we derived the sensor equation by modelling the geometric relationships between the LIDAR sub-modules, such as GPS, IMU, LS and the systematic errors associated with them. Based on this equation, we developed a program to generate simulated data with the system parameters, the systematic errors, the flight trajectories and attitudes, and the reference terrain model given. This program had been applied to generating simulated LIDAR data for urban areas. By analyzing these simulated data, we verified the accuracy and usefulness of the simulation. The simulator developed in this study will provide economically various test data required for the development of application algorithms and contribute to the optimal establishment of the flight and system parameters.

• Journal of Digital Contents Society
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• v.18 no.5
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• pp.989-994
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• 2017

In this paper, we propose a pothole detection system using 2D LiDAR and a pothole detection algorithm. Conventional pothole detection methods can be divided into vibration-based method, 3D reconstruction method, and vision-based method. Proposed pothole detection system uses two inexpensive 2D LiDARs and improves pothole detection performance. Pothole detection algorithm is divided into preprocessing for noise reduction, clustering and line extraction for visualization, and gradient function for pothole decision. By using gradient of distance data function, we check the existence of a pothole and measure the depth and width of the pothole. The pothole detection system is developed using two LiDARs, and the 3D pothole detection performance is shown by detecting a pothole with moving LiDAR system.

• Korean Journal of Optics and Photonics
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• v.30 no.3
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• pp.114-119
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• 2019

This paper discusses the development of a Raman lidar system for remote detection and measurement of hydrogen gas by using a photon counter. The Raman signal of the hydrogen gas is very weak and has a very low signal-to-noise ratio. The photon counter has the advantage of improving the signal-to-noise ratio, because it has a discriminator to eliminate the background noise from the Raman signal of the hydrogen gas. Therefore, a small and portable Raman lidar system was developed using a low-power pulsed laser and a photon-counter system to measure the hydrogen gas concentration remotely. To verify the capability of measuring hydrogen gas using the developed photon-counting Raman lidar system, experiments were carried out using a gas chamber in which it is possible to adjust the hydrogen gas concentration. As a result, our photon-counting Raman lidar system is seen to measure a minimum concentration of 0.65 vol.% hydrogen gas at a distance of 10 m.

• Korean Journal of Remote Sensing
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• v.36 no.6_3
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• pp.1681-1690
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• 2020

A scanning lidar system has been developed. The system has two wavelength observation channels of 532 and 1064 nm and is capable of 360-degree horizontal scanning observation. In addition, an analysis method that can classify the measured particle as an indicator of coarse-mode particle (PM2.5-10) and an indicator of fine-mode particles (PM2.5) and calculate the mass concentration of each has been developed by using the backscatter coefficient at two wavelengths. It was applied to the data calculated by observation. The mass concentrations of PM10 and PM2.5, which showed a distribution of 22-110 ㎍/㎥ and 7-78 ㎍/㎥, respectively, were successfully calculated in the Ulsan Onsan Industrial Complex using the developed scanning lidar system. The analyzed results showed similar values to the mass concentrations measured on the ground around the lidar observation area, and it was confirmed that high concentrations of 80-110 ㎍/㎥ and 60-78 ㎍/㎥ were measured at points discharged from factories, respectively.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.1
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• pp.174-192
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• 2021

The LIDAR sensor, which provides higher cognitive performance than cameras and radar, is difficult to apply to ADAS or autonomous driving because of its high price. On the other hand, as the price is decreasing rapidly, expectations are rising to improve existing autonomous driving functions by taking advantage of the LIDAR sensor. In level 3 autonomous vehicles, when a dangerous situation in the cognitive module occurs due to a sensor defect or sensor limit, the driver must take control of the vehicle for manual driving. If the driver does not respond to the request, the system must automatically kick in and implement a minimum risk maneuver to maintain the risk within a tolerable level. In this study, based on this background, a LIDAR-based LKS MRM algorithm was developed for the case when the normal operation of LKS was not possible due to troubles in the cognitive system. From point cloud data collected by LIDAR, the algorithm generates the trajectory of the vehicle in front through object clustering and converts it to the target waypoints of its own. Hence, if the camera-based LKS is not operating normally, LIDAR-based path tracking control is performed as MRM. The HAZOP method was used to identify the risk sources in the LKS cognitive systems. B, and based on this, test scenarios were derived and used in the validation process by simulation. The simulation results indicated that the LIDAR-based LKS MRM algorithm of this study prevents lane departure in dangerous situations caused by various problems or difficulties in the LKS cognitive systems and could prevent possible traffic accidents.