• Journal of Positioning, Navigation, and Timing
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• v.6 no.2
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• pp.79-86
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• 2017

Precise Point Positioning-Real Time Kinematic (PPP-RTK) refers to a technology that combines PPP with network-RTK in which a user does not directly receive observed data from a reference station but receives State-Space Representation (SSR) messages corrected for error components from a central processing station through Networked Transport of RTCM via Internet Protocol (NTRIP) or Digital Multimedia Broadcasting (DMB) for purposes of positioning. SSR messages, which refer to corrections used in PPP-RTK, are generated by a central processing station using real-time observed data collected from reference stations and account for corrections needed due to the ionosphere, troposphere, satellite orbital errors, satellite time offsets, and satellite biases. This study used a type of SSR message provided in South Korea, known as Korea-SSR (K-SSR), to implement a PPP-RTK algorithm based on code-pseudorange measurements and validated its accuracy within the reference station network. In order to validate the accuracy of the implemented algorithm outside of the network, the K-SSR was extrapolated and applied to positioning in reference stations in Changchun, China (CHAN) and Japan (AIRA). This also entailed a quantitative evaluation that measured improvements in accuracy in comparison with point positioning. The results of the study showed that positioning applied with extrapolated K-SSR correction data was more accurate in both AIRA and CHAN than point positioning with improvements of approximately 20~50%.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.6
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• pp.573-580
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• 2017

Precise stochastic modeling for GPS measurements is one of key factors in adjustment computations for GPS positioning. To analyze the GPS measurement errors, Minimum Norm Quadratic Unbiased Estimators(MINQUE) approach is used in this study to estimate the variance components for measurement types with short-baseline GPS positioning model. The results showed the magnitudes of measurement errors for C1, P2, L1, L2 are 22.3cm, 27.6cm, 2.5mm, 2.2mm, respectively. To reduce the memory usage and computational burden, variance components are also estimated on epoch-by-epoch basis. The results showed that there exists slight differences between the solutions. However, epoch-by-epoch analysis may also be used for most of GPS applications considering the magnitudes of the differences.

• Journal of the Korean Society for Precision Engineering
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• v.31 no.4
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• pp.319-326
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• 2014

Accurate estimation of the robot's position has an important role in autonomous navigation. Odometry is one of the most widely used techniques for mobile robot positioning. However, odometry has a well-known drawback that the position errors are accumulated when the travel distance increases. The UMBmark method is the conventional odometry calibration scheme for two wheel differential mobile robots. In the UMBmark method, the approximations for small angles are used in order to simplify the calculations. In this paper, we propose the new calibration scheme by using experimental orientation errors. Kinematic parameters can be calculated accurately without approximations by using experimental orientation errors. The numerical simulation and experimental results show that the odometry accuracy can be improved by the proposed method.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.29 no.2
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• pp.201-208
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• 2011

With the increase in the number of smartphone users, precise 3D positional information is required by various applications. The positioning accuracy using civilian single-frequency pseudoranges is at the level of 10 m or so, but most applications these days are asking for a sub-meter level Therefore, instead of an absolute positioning technique, the VRS-based differential approach is applied along with the correction of the double-differenced (DD) residual errors using FKP (Flachen-Korrektur-Parameter). The VRS (Virual Reference Station) is located close to the rover, and the measurements are generated by correcting the geometrical distance to those of the master reference station. Since the unmodeled errors are generally proportional to the length of the baselines, the correction parameters are estimated by fitting a plane to the DD pseudorange errors of the CORS network. The DD positioning accuracy using 24 hours of C/A code measurements provides the RMS errors of 37 cm, 28 cm for latitudinal and longitudinal direction, respectively, and 76 cm for height. The accuracy of the horizontal components is within ${\pm}0.5m$ for about 90% of total epochs, and in particular the biases are significantly decreased to the level of 2-3 cm due to the network-based error modeling. Consequently, it is possible to consistently achieve a sub-meter level accuracy from the single-frequency pseudoranges using the VRS and double-differenced error modeling.

• 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 Navigation and Port Research
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• v.39 no.3
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• pp.149-156
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• 2015

The Dynamic Positioning System consists of 7 elements which are namely Power system, Human machine interface, DP Computer, Position Reference System(PRS), Sensors, Thruster system and DP Operator. Incidents like loss of position(LOP) on DP vessel usually occur due to errors in these 7 elements. The purpose of this study is to find out safety operation method of DP vessel through qualitative and quantitative analyze of DP LOP incidents which are submitted to IMCA every year. The 612 DP LOP incidents submitted from 2001 to 2010 were analyzed to find out the main cause of the incidents and its rate among other causes. Consequently, the highest rate of incidents involving DP elements are PRS errors. DP computer, Power system, Human error and thruster system came next. The PRS has been analyzed and a flowchart was drawn through expert brainstorming. Also, the conditional probability has been analyzed through Bayesian Networks based on this flowchart. Consequentially, the main causes of drive off incidents were DGPS, microwave radar and HPR. Also, this study identified the main causes of DGPS errors through Bayesian Networks. These causes are signal blocked, electric components failure, relative mode error, signal weak or fail.

• Journal of International Society for Simulation Surgery
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• v.3 no.2
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• pp.87-89
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• 2016

Le fort 1 osteotomy surgery is one of the most popular surgical methods for the treatment of patients with facial bone deformities. An intermediate wafer splint is used to fix the bone segment to the planned position, but there are many steps that can cause errors. To reduce these errors, we propose a method of using a surgical guide made with virtual surgical simulation.

• Journal of Biomedical Engineering Research
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• v.44 no.2
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• pp.125-138
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• 2023

The development of AI systems for radiation therapy is important to improve the accuracy, effectiveness, and safety of cancer treatment. The current system has the disadvantage of monitoring patients using CCTV, which can cause errors and mistakes in the treatment process, which can lead to misalignment of radiation. Developed the PMRP system, an AI automation system that uses depth cameras to measure patient's fine movements, segment patient's body into parts, align Z values of depth cameras with Z values, and transmit measured feedback to positioning devices in real time, monitoring errors and treatments. The need for such a system began because the CCTV visual monitoring system could not detect fine movements, Z-direction movements, and body part movements, hindering improvement of radiation therapy performance and increasing the risk of side effects in normal tissues. This study could provide the development of a field of radiotherapy that lags in many parts of the world, along with the economic and social importance of developing an independent platform for radiotherapy devices. This study verified its effectiveness and efficiency with data through phantom experiments, and future studies aim to help improve treatment performance by improving the posture correction mechanism and correcting left and right up and down movements in real time.

• Journal of Platform Technology
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• v.12 no.1
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• pp.44-54
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• 2024

The existing indoor positioning methods using beacons or tags suffer from issues such as occasional undetection or increased errors due to noise. In this paper, we propose a method for determining the indoor position of a robot using the distance and, the angle between the direction of a target object whose position is known and the direction in which the robot views the target object from the front. The method proposed in this paper utilizes a depth camera to measure distance and calculate angles. Distance is measured using depth information captured by the camera, while angles are determined using images captured by the camera to determine the orientation of the target object. The proposed method calculates coordinate displacements using distance and angle. And then the method determines the position of the mobile robot using these displacements and the coordinates of the target object. To show the applicability of the proposed method for indoor positioning, we conducted experimental implementation and compared measured displacements. The results showed errors within 50mm, but considering the size of the mobile robot, it is judged that the method proposed in this paper can be sufficiently used for indoor positioning.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.1
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• pp.786-791
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• 2021

In this paper, in order to minimize limitations such as signal interference and positioning errors in existing indoor positioning systems, a smart LED-based positioning system for excellent line-of-sight radio environments and precise location tracking is proposed to improve accuracy. An IEEE 802.4 Zigbee module is mounted on the SMPS board of a smart LED; RSSI and LQI signals are received from a moving tag, and the system is configured to transmit the measured data to the positioning server through a gateway. For the experiment, the necessary hardware, such as the gateway and the smart LED module, were separately designed, and the experiment was conducted after configuring the system in an external field office. The positioning error was within 70cm as a result of performing complex calculations in the positioning server after transmitting a vector value of the moving object obtained from the direction sensor, together with a signal from the moving object received by the smart LED. The result is a significantly improved positioning error, compared to an existing short-range wireless communications-based system, and shows the level at which commercial products can be implemented.