• Journal of Astronomy and Space Sciences
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• v.25 no.3
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• pp.267-282
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• 2008

The GNSS (Global Navigation Satellite System) signal is delayed by the neutral atmosphere at the troposphere, so that the delay is one of major error sources for GNSS precise positioning. The tropospheric delay is an integrated refractive index along the path of GNSS signal. The refractive index is empirically related to standard meteorological variables, such as pressure, temperature and water vapor partial pressure, therefore the tropospheric delay could be calculated from them. In this paper, it is presented how to generate meteorological data where observation cannot be performed. KASI(Korea Astronomy & Space Science Institute) has operated 9 GPS (Global Positioning System) permanent stations equipped with co-located MET3A, which is a meteorological sensor. Meteorological data are generated from observations of MET3A by Ordinary Kriging. To compensate a blank of observation data, simple models which consider periodic characteristics for meteorological data, are employed.

• Journal of Information Technology Services
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• v.17 no.2
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• pp.83-100
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• 2018

Demand for stone products used as building materials is increasing. The construction industry, the value of the stone industry is sufficient, but the domestic stone industry is very lag regarding IT utilization. However, the overseas stone industry produces high-quality products using IT. In this study, we want to offer an IT application technology priority fit for the stone industries. We identify the current status and production process of the stone industries, then set the priority of various IT, so that obtain competitiveness in the domestic stone industries, and minimize the gap between the overseas stone industries. Therefore, we used AHP method; stone industry production processes were selected as the Enterprise Operation Management, Quarrying, Manufacturing, Construction and Maintenance of first-tier. The second-tier ones are consisted of 30 factors out of IT elements. Focus group interviews were conducted to confirm the validity of each factor. As a result, most important factors of first-tier was selected as the order of Manufacturing, Quarrying, Enterprise Operation Management, and Construction & Maintenance. The top 5 of 30 factors in the second-tier were selected Smart Sensor, Mobile Device, Robot of manufacturing, GIS of quarrying, and SCM of enterprise operation management. And the factor that relatively less important was GPS of construction and maintenance. If properly applied an IT application technology for stone industry, we expect to provide efficient production lines and increase customer satisfaction, which will ultimately expand the promotion for the industry and thus act as positive factor in promoting the stone industry.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.344-346
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• 2004

IKONOS 1m satellite imagery is particularly well suited for 3-D feature extraction and 1 :5,000 scale topographic mapping. Because the image line and sample calculated by given RPCs have the error of more than 11m, in order to be able to perform feature extraction and topographic mapping, rational polynomial coefficients(RPCs) camera model that are derived from the very complex IKONOS sensor model to describe the object-image geometry must be refined by several Ground Control Points(GCPs). This paper presents a quantitative evaluation of the geometric accuracy that can be achieved with IKONOS imagery by refining the offset and scaling factors of RPCs using several GCPs. If only two GCPs are available, the offsets and scale factors of image line and sample are updated. If we have more than three GCPs, four parameters of the offsets and scale factors of image line and sample are refined first, and then six parameters of the offsets and scale factors of latitude, longitude and height are updated. The stereo images acquired by IKONOS satellite are tested using six ground points. First, the RPCs model was refined using 2 GCPs and 4 check points acquired by GPS. The results from IKONOS stereo images are reported and these show that the RMSE of check point acquired from left images and right are 1.021m and 1.447m. And then we update the RPCs model using 4 GCPs and 2 check points. The RMSE of geometric accuracy is 0.621 m in left image and 0.816m in right image.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.220-223
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• 2004

Automatic image registration is an essential element of remote sensing because remote sensing system generates enormous amount of data, which are multiple observations of the same features at different times and by different sensor. The general process of automatic image registration includes three steps: 1) The extraction of features to be used in the matching process, 2) the feature matching strategy and accurate matching process, 3) the resampling of the data based on the correspondence computed from matched feature. For step 2) and 3), we have developed an algorithms for automated registration of satellite images with RANSAC(Random Sample Consensus) in success. However, for step 1), There still remains human operation to generate GCP Chips, which is time consuming, laborious and expensive process. The main idea of this research is that we are able to automatically generate GCP chips with comer detection algorithms without GPS survey and human interventions if we have systematic corrected satellite image within adaptable positional accuracy. In this research, we use SUSAN(Smallest Univalue Segment Assimilating Nucleus) algorithm in order to detect the comer. SUSAN algorithm is known as the best robust algorithms for comer detection in the field of compute vision. However, there are so many comers in high-resolution images so that we need to reduce the comer points from SUSAN algorithms to overcome redundancy. In experiment, we automatically generate GCP chips from IKONOS images with geo level using SUSAN algorithms. Then we extract reference coordinate from IKONOS images and DEM data and filter the comer points using texture analysis. At last, we apply automatically collected GCP chips by proposed method and the GCP by operator to in-house automatic precision correction algorithms. The compared result will be presented to show the GCP quality.

• Journal of Positioning, Navigation, and Timing
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• v.6 no.4
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• pp.181-194
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• 2017

In recent years, research has been actively conducted on the navigation in an indoor environment where Global Navigation Satellite System signals are unavailable. Among them, a study performed indoor navigation by integrating pseudolite carrier and Inertial Measurement Unit (IMU) sensor. However, in this case, there was no solution for the cycle slip occurring in the carrier. In another study, cycle slip detection and compensation were performed by integrating Global Positioning System (GPS) and IMU in an outdoor environment. However, in an indoor environment, cycle slip occurs more easily and frequently, and thus the occurrence of half cycle slip also increases. Accordingly, cycle slip detection based on 1 cycle unit has limitations. Therefore, in the present study, the aforementioned problems were resolved by performing indoor navigation through the integration of pseudolite and ultra-low-cost IMU embedded in a smartphone and by performing half cycle slip detection and compensation based on this. In addition, it was verified through the actual implementation of real-time navigation.

• Journal of Positioning, Navigation, and Timing
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• v.6 no.4
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• pp.195-203
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• 2017

A 2U cube satellite called SNUGLITE has been developed by GNSS Research Laboratory in Seoul National University. Its main mission is to perform actual operation by mounting dual-frequency global positioning system (GPS) receivers. Its scientific mission aims to observe space environments and collect data. It is essential for a cube satellite to control an Earth-oriented attitude for reliable and successful data transmission and reception. To this end, an attitude estimation and control algorithm, Attitude Determination and Control System (ADCS), has been implemented in the on-board computer (OBC) processor in real time. In this paper, the Extended Kalman Filter (EKF) was employed as the attitude estimation algorithm. For the attitude control technique, the Linear Quadratic Gaussian (LQG) was utilized. The algorithm was verified through the processor in the loop simulation (PILS) procedure. To validate the ADCS algorithm in the ground, the experimental verification via a single axis Hardware-in-the-loop simulation (HILS) was used due to the simplicity and cost effectiveness, rather than using the 3-axis HILS verification (Schwartz et al. 2003) with complex air-bearing mechanism design and high cost.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.3
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• pp.1191-1202
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• 2013

The former researches on earthwork automation were mainly focused on GPS and sensor application, environment modelling, equipment path planning, work information management, and remote control etc. Recently, reducing $CO_2$ emission becomes one of main focuses for an automation research. In the case of earthwork operations, many kinds of construction machines or robots are involved, which can cause high level of $CO_2$ in a construction site. An effective earthwork plan and construction machine operation can both increase productivity and safety and decrease $CO_2$ emission level. In this research, some automation concepts for green earthworks are suggested such as a 3D construction site model, a 3D earthwork distribution based on two different earthwork methods, and an earthwork package construction method. A excel-based simulator is developed to generate the 3D earthwork distribution and to estimate the level of $CO_2$ emission for the given earthwork.

• Journal of Biosystems Engineering
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• v.35 no.2
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• pp.77-84
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• 2010

In this study, we tried to predict tractor power output, fuel consumption rate and work performance indirectly in order to develop an eco driving system. Firstly, we developed equations which could predict tractor power output and fuel consumption rate using characteristic curves of tractor power output. Secondly, with actual engine rpm determined by initial engine rpm and work load, tractor power output and fuel consumption rate were forecasted. Thirdly, with speed signals of GPS sensor system, it was possible to foresee tractor work performance and fuel consumption rate. Lastly, precision of the eco driving system was evaluated through tractor PTO test, and effects of the eco driving system were investigated in the plowing and rotary tilling operations. Engine rpm, power output, fuel consumption rate, work performance and fuel consumption rate per plot area were displayed in the eco driving system. Predicted tractor power outputs in the full load curve were well coincided with the actual power output of prototype, but small differences, 1 to 6 ㎾, were found in the part load curve. Error of the fuel consumption rate was 0.5 L/h, 4.5%, the greatest, and 1 to 3 L/h at the part load curve. It was shown that 69% and 53% of fuel consumption rates could be reduced in plowing and rotary tilling operations, respectively, when the eco driving system was installed in tractor.

• Journal of Astronomy and Space Sciences
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• v.35 no.3
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• pp.185-193
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• 2018

Jang Bogo Station (JBS), the second Korean Antarctic research station, was established in Terra Nova Bay, Antarctica ($74.62^{\circ}S$ $164.22^{\circ}E$) in February 2014 in order to expand the Korea Polar Research Institute (KOPRI) research capabilities. One of the main research areas at JBS is space environmental research. The goal of the research is to better understand the general characteristics of the polar region ionosphere and thermosphere and their responses to solar wind and the magnetosphere. Ground-based observations at JBS for upper atmospheric wind and temperature measurements using the Fabry-Perot Interferometer (FPI) began in March 2014. Ionospheric radar (VIPIR) measurements have been collected since 2015 to monitor the state of the polar ionosphere for electron density height profiles, horizontal density gradients, and ion drifts. To investigate the magnetosphere and geomagnetic field variations, a search-coil magnetometer and vector magnetometer were installed in 2017 and 2018, respectively. Since JBS is positioned in an ideal location for auroral observations, we installed an auroral all-sky imager with a color sensor in January 2018 to study substorms as well as auroras. In addition to these observations, we are also operating a proton auroral imager, airglow imager, global positioning system total electron content (GPS TEC)/scintillation monitor, and neutron monitor in collaboration with other institutes. In this article, we briefly introduce the observational activities performed at JBS and the preliminary results of these observations.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.6_1
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• pp.549-557
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• 2012

Spatial phenomena such as environment pollution, disease and the risk of spreading information need a rapid initial response to perceive spread event. Moving data perceive spread event through real-time processing and analysis. To process and analysis the event, spatial-temporal complex event processing is used. Previous spatialtemporal complex event processing is possible basis spatial operator but insufficient apply to design spatialtemporal complex event processing to perceive spatial phenomena of high complexity. This study proposed hierarchical spatio-temporal CEP design which will efficiently manage the fast growing incoming sensor data. The implementation of the proposed design is evaluated with GPS location data of moving vehicles which are used as the incoming data stream for identifying spatial events. The spatial component of existing CEP software engine has been extended during the implementation phase to broaden the capabilities of processing spatio-temporal events.