• Korean Journal of Remote Sensing
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• v.36 no.4
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• pp.645-652
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• 2020

GK2A(GEO-KOMPSAT-2A)satellite has been operating excellently since its launch in Dec 2018. The secondary payload called KSEM (Korean Space Environment Monitor) was equipped into the GK2A satellite along with AMI (Advanced Meteorological Imager) sensor. KSEM is the Korea's first operational geostationary space weather sensor and has been developed collaboratively by KHU (Kyung Hee University) and KARI (Korea Aerospace Research Institute). The interface works between KSEM and GK2A were conducted by KARI. Various interface tests, which aim for evaluating effective functionality of KSEM with the spacecraft, were intensively conducted at KARI facilities. Main tests consisted of mechanical and electrical check-up activities between the KSEM and GK2A. Interface tests of KSEM, which involve pre-launch tests such as ETB and GK2A system level tests, were conducted to evaluate functional and performance of KSEM before the launch. The tests carried out during the GK2A LEOP (Launch and Early Orbit Phase) and IOT (In Orbit Test) period (Dec 2018 ~ June 2019) showed excellent in-orbit performance of KSEM data.

• Bulletin of the Korean Space Science Society
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• 2004.10b
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• pp.296-299
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• 2004

KARI precision attitude determination system has been developed for high accurate geo-coding of KOMPSAT-2 image. Sensor data from two star trackers and a IRU are used as measurement and dynamic data. Sensor data from star tracker are composed of QUEST and unit vector filter. Filter algorithms consists of extended Kalman filter, unscented Kalman filter, and least square batch filter. The type of sensor data and filter algorithm can be chosen by user options. Estimated parameters are Euler angle from 12000 frame to optical bench frame, gyro drift rate bias, gyro scale factor, misalignment angle of star tracker coordinate frame with respect to optical bench frame, and misalignment angle of gyro coordinate frame with respect to optical bench frame. In particular, ground control point data can be applied for estimating misalignment angle of star tracker coordinate frame. Through the simulation, KPADS is able to satisfy the KOMPSAT-2 mission requirement in which geo-location accuracy of image is 80 m (CE90) without ground control point.

• Journal of the Korean GEO-environmental Society
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• v.15 no.12
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• pp.71-77
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• 2014

Heavy rainfall induces many disasters including slope failure and infrastructure collapse. In this point of view, rainfall-simulated centrifugal model test can be a reasonable tool to evaluate the stability of geotechnical structure. In order to obtain the displacements of a model in centrifugal model test, in general, LVDT and laser displacement sensor are used. However, when the rainfall is simulated, the LVDT has the problem of excessive infiltration into the model ground, and the laser displacement sensor provides the measuring result with inaccuracy due to the dispersion of the laser radiation. Hence, in this study, horizontal displacement sensor for rainfall-simulated centrifugal model test was developed. This sensor produced with a thin elastic steel plate and gave the accurate relationship between the displacement and the strain.

• Journal of the Korean GEO-environmental Society
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• v.20 no.1
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• pp.19-25
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• 2019

In this present study, to evaluate the applicability of the monitoring system of the entire reservoir dam facility using the wireless sensor network system and a section representative of the domestic reservoir dam was selected as the test bed site and to operated a system that can evaluate the condition of the facility at the real time with monitoring. In order to set up a wireless sensor network system, the system assessment of present state was carried out for confirmation the risk factors and the limit values of the risk factors in limit state were calculated. The type and position of the sensor to be measured in the field were determined by setting the measurement items suitable for the hazardous area and the risk factor. In this paper, we evaluated the feasibility of the system by monitoring and constructing a wireless sensor network system in a field for a fill dam that can represent a domestic reservoir dam. Applicability evaluation was verified by comparing directly with the measurement of partial concentration method which is the measurement management technology of the dam.

• Spatial Information Research
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• v.23 no.3
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• pp.91-100
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• 2015

We developed a micro UAV based rapid mapping system that provides geospatial information of target areas in a rapid and automatic way. Users can operate the system easily although they are inexperienced in UAV operation and photogrammetric processes. For the aerial data acquisition, we constructed a micro UAV system mounted with a digital camera, a GPS/IMU, and a control board for the sensor integration and synchronization. We also developed a flight planning software and data processing software for the generation of geo-spatial information. The processing software operates automatically with a high speed to perform data quality control, image matching, georeferencing, and orthoimage generation. With the system, we have generated individual ortho-images within 30 minutes from 57 images of 3cm resolution acquired from a target area of $400m{\times}300m$.

• Journal of the Korean Association of Geographic Information Studies
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• v.26 no.4
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• pp.116-129
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• 2023

Recently, interest in autonomous driving has drawn attention to autonomous cooperative driving, which considers the development of driving technology of autonomous vehicles and the development of infrastructure that constitutes a driving environment. According to the concept of autonomous cooperative driving, This study analyzes the new infrastructure for autonomous driving that can complement the information of existing precise road maps and adding HD map layer as the new infrastructure. The new infrastructure for autonomous driving presented two types of improved facilities and one type of sensor only facility. Analysis of HD maps shows that information such as junction points rarely changes, but it is expected that infrastructure for autonomous driving can be added to convey the meaning of paying attention to obstacles that may arise at the junction. In this way, the new infrastructure for autonomous driving needs to support the roles of guidance, instruction, and attention that existing road facilities.

• Aerospace Engineering and Technology
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• v.9 no.2
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• pp.22-30
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• 2010

KARI had integrated and tested GEO satellite in cooperation with Astrium Inc., France. In the middle of integration and test, It was necessary to check GEO satellite SA(solar array) status and require electrical interface verification with bus. SA of GEO satellite have different mechanical characteristics in comparison with those of LEO satellite which was tested in KARI. LEO SA has been deployed by simple mechanical hinge system but GEO SA has been done by more complicated method. so in this paper, we designed the test configuration and analyzed the test result of solar array electrical integration of GEO satellite.

• Journal of the Korea Society of Computer and Information
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• v.29 no.1
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• pp.21-30
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• 2024

In this paper, we propose a method to build a sample dataset of the features of eight sensor-only facilities built as infrastructure for autonomous cooperative driving. The feature extracted from point cloud data acquired by LiDAR and build them into the sample dataset for recognizing the facilities. In order to build the dataset, eight sensor-only facilities with high-brightness reflector sheets and a sensor acquisition system were developed. To extract the features of facilities located within a certain measurement distance from the acquired point cloud data, a cylindrical projection method was applied to the extracted points after applying DBSCAN method for points and then a modified OTSU method for reflected intensity. Coordinates of 3D points, projected coordinates of 2D, and reflection intensity were set as the features of the facility, and the dataset was built along with labels. In order to check the effectiveness of the facility dataset built based on LiDAR data, a common CNN model was selected and tested after training, showing an accuracy of about 90% or more, confirming the possibility of facility recognition. Through continuous experiments, we will improve the feature extraction algorithm for building the proposed dataset and improve its performance, and develop a dedicated model for recognizing sensor-only facilities for autonomous cooperative driving.

• Journal of the Korean GEO-environmental Society
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• v.19 no.1
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• pp.25-30
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• 2018

Conventional monitoring method is used for evaluation of the reservoir and levee at the highest height sections. In recent years, automated measurement technology has been developed, and the measurement results are transmitted, collected and stored in real time into management office. Despite the development of real time monitoring technology, the measurement results are not used directly or indirectly with facility management at real time. Recently, as wireless sensor network measurement technology has been developed based on internet of things, this study proposed a real - time measurement and evaluation system based on wireless sensor network technology in the reservoir structure. As a result of the seepage analysis for the application, it was confirmed that the volumetric water content changes together with the change of the seepage line inside the embankment body according to the change of the water level of the embankment. In other words, the applicability of the measurement system with the volumetric water ratio set as the sensor node was verified.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.388-393
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• 2002

Remote sensing data is collected and analyzed to enhance understanding of the terrestrial surface. Since Landsat satellite was launched in 1972, many researches using multispectral data has been achieved. Recently, with the availability of airborne and satellite hyperspectral data, the study on hyperspectral data are being increased. It is known that as the number of spectral bands of high-spectral resolution data increases, the ability to detect more detailed cases should also increase, and the classification accuracy should increase as well. In this paper, we classified the hyperspectral and multispectral data and tested the classification accuracy. The MASTER(MODIS/ASTER Airborne Simulator, 50channels, 0.4~13$\mu$m) and Landsat TM(7channels) imagery including Yeong-Gwang area were used and we adjusted the classification items in several cases and tested their classification accuracy through statistical comparison. As a result of this study, it is shown that hyperspectral data offer more information than multispectral data.