• Proceedings of the KSR Conference
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• 2006.11b
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• pp.802-810
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• 2006

For a thorough train control, the precise train position detection is necessarily required. The widely used current way for train position detection is the one of using track circuits. The track circuit has a simple structure, and has a high level of reliability. However trains can be detected only on track circuits, which have to be installed on all ground sections, and much amount of cost for its installation and maintenance is needed. In addition, for the track circuit, only discontinuous position detection is possible because of the features of the closed circuit loop configuration. As the recent advances in telecommunication technologies and high-tech vehicle-based control equipments, for the train position detection, the method to detect positions directly from on trains is being studied. Vehicle-based position detection method is to estimate train positions, speed, timing data continuously, and to use them as the control information. In this paper, the features of GPS navigation and DR navigation are analyzed, and the navigation filters are designed by constructing vehicle-based train position detection method by combining GPS navigation and DR navigation for their complementary cooperation, and by using kalman filter. The position estimation performance of the proposed method is also confirmed by simulations.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.40 no.12
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• pp.1032-1039
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• 2012

The present paper deals with precise relative positioning of formation satellites with long baseline in low Earth orbit making use of L1/L2 dual frequency GPS carrier phase measurements. Kinematic approach means to describe the motion of objects without taking its mass/dynamics model into consideration. The advantage of the kinematic approach is that information about dynamics of the system is not applied, which gives more flexibility and could improve the scientific interest of the observations made by the mission. The ionosphere terms, which are not canceled by double differenced measurement equation in the case of the long baseline, are explicitly estimated as unknown parameters by extended Kalman filter. The estimated float ambiguities by EKF are solved by existing efficient integer vector search strategy under integer least square condition. For the integer vector search, we employ well known MLAMBDA. Finally, The feasibility and accuracy of processing scheme are demonstrated using the GPS measurements for two satellites in low Earth orbit separated by baselines of 100 km.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.10
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• pp.609-617
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• 2016

In general, Personal Navigation Systems (PNSs) can be defined systems to acquire pedestrian positional information. GPS is an example of PNS. However, GPS can only be used where the GPS signal can be received. Pedestrian Dead Reckoning (PDR) can estimate the positional information of pedestrians using Inertial Measurement Unit (IMU). Therefore, PDR can be used for GPS-disabled areas. This paper proposes a PDR scheme considering various movement types over GPS-disabled areas as combat environments. We propose a movement distance estimation scheme and movement direction estimation scheme as pedestrian's various movement types such as walking, running and crawling using IMU. Also, we propose a fusion algorithm between GPS and PDR to mitigate the lack of accuracy of positional information at the entrance to the building. The proposed algorithm has been tested in a real test bed. In the experimental results, the proposed algorithms exhibited an average position error distance of 5.64m and position error rate in goal point of 3.41% as a pedestrian traveled 0.6km.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.6
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• pp.175-182
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• 2020

The non-contact eye tracking is a nonintrusive human-computer interface providing hands-free communications for people with severe disabilities. Recently. it is expected to do an important role in non-contact systems due to the recent coronavirus COVID-19, etc. This paper proposes a novel approach for an eye mouse using an eye tracking method based on a context-aware based AdaBoost multi-region classifier and ASSL algorithm. The conventional AdaBoost algorithm, however, cannot provide sufficiently reliable performance in face tracking for eye cursor pointing estimation, because it cannot take advantage of the spatial context relations among facial features. Therefore, we propose the eye-region context based AdaBoost multiple classifier for the efficient non-contact gaze tracking and mouse implementation. The proposed method detects, tracks, and aggregates various eye features to evaluate the gaze and adjusts active and semi-supervised learning based on the on-screen cursor. The proposed system has been successfully employed in eye location, and it can also be used to detect and track eye features. This system controls the computer cursor along the user's gaze and it was postprocessing by applying Gaussian modeling to prevent shaking during the real-time tracking using Kalman filter. In this system, target objects were randomly generated and the eye tracking performance was analyzed according to the Fits law in real time. It is expected that the utilization of non-contact interfaces.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.1D
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• pp.135-143
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• 2009

Integrating the Global Positioning System (GPS) and Inertial Navigation System (INS) sensor technologies using the precise GPS Carrier phase measurements is a methodology that has been widely applied in those application fields requiring accurate and reliable positioning and attitude determination; ranging from 'kinematic geodesy', to mobile mapping and imaging, to precise navigation. However, such integrated system may not fulfil the demanding performance requirements when the baseline length between reference and mobil user GPS receiver is grater than a few tens of kilometers. This is because their positioning/attitude determination is still very dependent on the errors of the GPS observations, so-called "baseline dependent errors". This limitation can be remedied by the integration of GPS and INS sensors, using multiple reference stations. Hence, in order to derive the GPS distance dependent errors, this research proposes measurement processing algorithms for multiple reference stations, such as a reference station ambiguity resolution procedure using linear combination techniques, a error estimation based on Kalman filter and a error interpolation. In addition, all the algorithms are evaluated by processing real observations and results are summarized in this paper.

• Journal of Advanced Navigation Technology
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• v.26 no.6
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• pp.404-411
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• 2022

The main function in operating the satellite navigation system is to accurately determine the orbit of the navigation satellite and transmit it as a navigation message. In this study, we developed software to determine the orbit of a navigation satellite by combining an extended Kalman filter and an accurate dynamic model. Global positioning system (GPS) and quasi-zenith satellite system (QZSS) orbit determination was performed using international gnss system (IGS) ground station observations and user range error (URE), a key performance indicator of the navigation system, was calculated by comparison with IGS precise ephemeris. When estimating the clock error mounted on the navigation satellite, the radial orbital error and the clock error have a high inverse correlation, which cancel each other out, and the standard deviations of the URE of GPS and QZSS are small namely 1.99 m and 3.47 m, respectively. Instead of estimating the clock error of the navigation satellite, the orbit was determined by replacing the clock error of the navigation message with a modeled value, and the regional correlation with URE and the effect of the ground station arrangement were analyzed.