• Journal of Digital Convergence
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• v.17 no.10
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• pp.461-468
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• 2019

The aim of this study was to compare and analyse the national players between the winning games and the losing ones by classifying the GPS data measured in the competition. 27 players of Korean national team on field hockey had analysed to collect plenty of data by using GPS system in real time on 16 A-matches for this paper. The result was followed: First, it has revealed that the winning games showed that it had played a lot in the rest of the zone except for zone 1 and zone 5 from zone 1 to zone 6. Second, is has also shown that it had a significant differences into the distance between the winning games and the losing ones. Third, there were no significant differences between Low-speed zone (zone 1 to Zone 3) and High-speed zone (zone 4 to zone 6) into the distance but were a significant differences on the number of high-accelerations in a section of accelerations. Last, in the position-specific, it has shown a significant differences between a distance by the section and the acceleration frequency and the results showed that the difference between the low accelerations and high ones influenced positively related to the performance.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.43 no.1
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• pp.79-87
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• 2015

In this paper, a real time on-board orbit determination method using the extended kalman filter is suggested and its performance is analyzed in the environment of the orbit. Considering the limited on-board resources, the $J_2$ orbit propagate model and the GPS navigation solution are used for on-board orbit determination. The analysis result of the on-board orbit determination method implemented in DubaiSat-2 showed that position and velocity error are improved from 70.26 m to 26.25 m and from 3.6 m/s to 0.044 m/s, respectively when abnormal excursion errors is removed in the GPS navigation solution.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.12
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• pp.2730-2736
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• 2010

Recently, various networks have been introduced in the car of the internal and external sides. These have been integrated by one HMI(Human Machine Interface) to control devices of each network and provide information service. The existing vehicle navigation system, providing GPS based vehicle positioning service, has been included to these integrated networks as a default option. The GPS has been used to the most universal device to provide position information by using satellites' signal. But It is impossible to provide the position information when the GPS can't receive the satellites' signal in the area of tunnel, urban canyon, or forest canopy. Thus, this paper propose and implement the method of measuring vehicle position by using the sensing data of internal CAN network and external Wi-Fi network of the integrated car navigation circumstances when the GPS doesn't work normally. The results obtained by implementation shows the proposed method works well by map matching.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.9
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• pp.4587-4592
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• 2013

GPS is recognized the essential method to obtain the best result in the sphere of earth science that is setting of International Reference Frame, decision of the rotation coefficient about the earth rotation axis, detection of the crustal deformation, and observation of the diastrophism by high precision positioning except for navigation, geodetic survey and mapping. Therefore, in this study, it was attempted to build an expert service that enables non-experts to use high-precision GPS data processing. As a result, an Precise Point Positioning Solution that can maximize user convenience simply by entering the minimum required information for GPS data processing was developed, and the result of Precise Point Positioning Solution using GPS data provided by National Geographic Information Institute was compared with result of ITRF.

• Journal of Advanced Navigation Technology
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• v.23 no.3
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• pp.221-227
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• 2019

In this paper, interacting multiple model (IMM) filter was designed that guarantees a stable navigation performance even in the unstable satellite navigation position. In order to design IMM filter in INS / GPS integrated navigation system, sub filter of the IMM filter is defined as Kalman filter. In the IMM filter configuration, two subfilters are determined. Each Kalman filter defines the six-teenth state composed of position, velocity, attitude, and sensor error from the INS error equation and the states additionally derived in case of the coloured measurement noise. In order to verify the performance of the proposed filter, we compared the performance how the filter works in the presence of arbitrary error in GPS navigation solution. The Monte Carlo simulation was performed 100 times and the results were compared with the root mean square(RMS). The results show that the proposed method is stable against errors and show fast convergence.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.6
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• pp.164-175
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• 2019

Installation of digital tachograph, black box, and ADAS have been enforced to commercial vehicles for preventing violent driving and accidents by the Traffic Safety Act in Korea. Nevertheless, the damage caused by road hazards has increased 1.5 times in 2016 compared to 2013. So, developing new technologies that can identify road hazard using the sensors installed in commercial vehicles are conducting by the Ministry of Land, Infrastructure and Transport. As a part of the technologies, this research analyze the error range of GPS installed in commercial vehicles that vary according to the driving speed. As a result, the average error was 9.72m at the driving speed of 100km/h, and the error was 2.1 times larger than the average error of 4.69m at the driving speed of 40km/h. The event point proper integration/separation range(m) was analyzed to be 20m with a recognition rate of 90% or more at the same point regardless of driving speed. The results of this research can be used as basic data for improving the accuracy of location-based data would be collected using commercial vehicles.

• Journal of the Korea Society of Computer and Information
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• v.25 no.6
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• pp.91-98
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• 2020

In order to prevent a collision accident during sudden braking, we have proposed an hazard lamps automatic operation system that can be easily installed in existing vehicles that do not have hazard lamps automatic operation. There are several ways to recognize sudden braking. Using GPS, the system does not work in a tunnel, and it is difficult to install the system additionally on an existing vehicle using a vehicle speed sensor. Therefore, the proposed system eliminates these problems by using the acceleration sensor and makes it possible to recognize even the sudden turning and bounce of the vehicle.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.31 no.5
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• pp.375-384
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• 2013

Most of regions within the city of Mokpo, located on the southwest coast of the Korean Peninsula, are subjected to significant subsidence because about 70% of the city is land reclaimed from the sea (Kim et al., 2005). In this study, we aimed to estimate the rate of subsidence over Mokpo by using PALSAR L-band dataset from 2006 to 2010. Time series analysis was performed as well using GPS surveying data from 2010 to 2012. Results from these two independent datasets are then compared and analyzed over the common period of time. GPS data processing provides the results of seasonal variation on the surface, that is, via repeatedly rising and falling in association with the periodic cycle. Therefore, a time series analysis was performed to calculate the rate of ground subsidence. The deformation rates calculated for the same point are 3.89cm/yr and 2.65cm/yr from the GPS data and SAR data, respectively. SAR and GPS data processing results show a very similar pattern in terms of magnitude of annual subsidence. Thus, if the two datasets are integrated together, new modeling on ground subsidence is feasible. Lastly, subsidence was detected in a landfill area in the city of Mokpo, which has been continuously occurring through 2012.

• Journal of the Korea Society of Computer and Information
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• v.28 no.1
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• pp.49-54
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• 2023

The Global Positioning System (GPS) was developed for military purposes and developed as it is today by opening civilian signals (GPS L1 frequency C/A signals). The current satellite orbits the earth about twice a day to measure the position, and receives more than 3 satellite signals (initially, 4 to calculate even the time error). The three-dimensional position of the ground receiver is determined using the data from the radio wave departure time to the radio wave Time of Arrival(TOA) of the received satellite signal through trilateration. In the case of navigation using GPS in recent years, a location error of 5 to 10 m usually occurs, and quite a lot of areas, such as apartments, indoors, tunnels, factory areas, and mountainous areas, exist as blind spots or neutralized areas outside the error range of GPS. Therefore, in order to acquire one's own location information in an area where GPS satellite signal reception is impossible, another method should be proposed. In this study, IMU(Inertial Measurement Unit) combined with an acceleration and gyro sensor and a geomagnetic sensor were used to design a system to enable location recognition even in terrain where GPS signal reception is impossible. A method to track the current position by calculating the instantaneous velocity value using a 9-DOF IMU and a geomagnetic sensor was studied, and its feasibility was verified through production and experimentation.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.9 no.3
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• pp.73-84
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• 2010

This study presents a novel method to identify hazardous segments of freeway using global positioning system(GPS) based probe vehicle data. A variety of candidate contributing factors leading to higher potential of accident occurrence were extracted from the probe vehicle dataset. The research problem was defined as a classification problem, then a well-known classifier, bayesian neural network was adopted to solve the problem. A binary logistic regression technique was also used for selecting salient input variables. Test results showed that the proposed method is promising in extracting hazardous freeway sections. The outcome of this study will be effectively used for evaluating the safety of freeway sections and deriving countermeasures to prevent accidents.