• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1125-1139
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• 2022

In an unmanned aerial vehicles (UAVs) system, a physical offset can be existed between the global positioning system/inertial measurement unit (GPS/IMU) sensor and the observation sensor such as a hyperspectral sensor, and a lidar sensor. As a result of the physical offset, a misalignment between each image can be occurred along with a flight direction. In particular, in a case of multi-sensor system, an observation sensor has to be replaced regularly to equip another observation sensor, and then, a high cost should be paid to acquire a calibration parameter. In this study, we establish a precise sensor model equation to apply for a multiple sensor in common and propose an independent physical offset estimation method. The proposed method consists of 3 steps. Firstly, we define an appropriate rotation matrix for our system, and an initial sensor model equation for direct-georeferencing. Next, an observation equation for the physical offset estimation is established by extracting a corresponding point between a ground control point and the observed data from a sensor. Finally, the physical offset is estimated based on the observed data, and the precise sensor model equation is established by applying the estimated parameters to the initial sensor model equation. 4 region's datasets(Jeon-ju, Incheon, Alaska, Norway) with a different latitude, longitude were compared to analyze the effects of the calibration parameter. We confirmed that a misalignment between images were adjusted after applying for the physical offset in the sensor model equation. An absolute position accuracy was analyzed in the Incheon dataset, compared to a ground control point. For the hyperspectral image, root mean square error (RMSE) for X, Y direction was calculated for 0.12 m, and for the point cloud, RMSE was calculated for 0.03 m. Furthermore, a relative position accuracy for a specific point between the adjusted point cloud and the hyperspectral images were also analyzed for 0.07 m, so we confirmed that a precise data mapping is available for an observation without a ground control point through the proposed estimation method, and we also confirmed a possibility of multi-sensor fusion. From this study, we expect that a flexible multi-sensor platform system can be operated through the independent parameter estimation method with an economic cost saving.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.1883-1886
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• 2005

In this paper, a decoupled dual servo (DDS) stage for ultra-precision scanning system with large working range is introduced. In general, dual servo systems consist of a fine stage for short range and a coarse stage for long range. The proposed DDS also consists of a $XY\theta$ fine stage for handling and carrying workpieces and one axis coarse stage. Its coarse stage consists of air bearing guide system and a coreless linear motor with force ripple. The fine has four voice coil motors(VCM) as its actuator. According to a VCM's nature, there are no mechanical connections between coils and magnetic circuits. Moreover, VCM doesn't have force ripples due to imperfections of commutation components of linear motor systems - currents and flux densities. However, due to the VCM's mechanical constraints the working range of the fine is about $25mm^2$. To break that hurdle, the coarse stage with linear motors is used to move the fine about 500mm. Because of the above reasons, the proposed DDS can achieve higher precision scanning than other stages with only one servo. With MATLAB's Sequential Quadratic Programming (SQP), the VCMs are optimally designed for the highest force under conditions and constraints such as thermal dissipations due to its coil, its size, and so on. And for their movements without any frictions, guide systems of the DDS are composed of air bearings. To get precisely their positions, a linear scale with 5nm resolution are used for the coarse stage's motion and three plane mirror laser interferometers with 5nm for the fine's $XY\theta$ motions. With them, on scanning the two stages have same trajectories. The control algorithm is named Parallel method. The embodied ultra-precision scanning system has sub 100nm following error and in-positioning stability.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.32 no.2
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• pp.163-171
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• 2014

Based on the GPS/IMU integration, the car navigation has unstable conditions as well as drastically reduces accuracies in urban region. Nowadays, many cars mounted the camera to record driving states. If the ground coordinates of street furniture are known, the position and attitude of camera can be determined through SPR(Single Photo Resection). Therefore, an estimated position and attitude from SPR can be applied measurements in Kalman filter for updating errors of navigation solutions from GPS/IMU integration. In this study, the GPS/IMU/SPR integration algorithm was developed in loosely coupled modes through extended Kalman filters. Also, in order to analyze performances of GPS/IMU/SPR, simulation tests were conducted in GPS signal reception environments and the GCPs (Ground Control Points) distributions. In fact, the position and attitude gathered from GPS/IMU/SPR integration are more precise than the position and attitude from GPS/IMU integration. When IPs (image points), corresponded to GCPs, were concentrated in the center of image, the position error in the optical axis respectively increased. To understand effects from SPR, we plan to carry additional test on the magnitude of GCP, IP and initial exterior orientation errors.

• The Journal of Korean Society for Radiation Therapy
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• v.27 no.2
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• pp.123-129
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• 2015

Purpose : The goal of this study was to verify and analyze the source position according to the curvature of the universal applicator and 4 different angle applicators when using RALS(Remote After Loading System). Materials and Methods : An interval of 1 cm and 15 second dwell times in each source position were applied for plan. To verify the accuracy of source position, we narrowed the distance between MultiSource container and GAFCHROMIC$^{(R)}$ EBT3 film by 5 cm, 10 cm, 20 cm so that the universal applicator transfer tube had some curvature. Also 4 applicators(Intrauterine tube: $0^{\circ}$, $15^{\circ}$, $30^{\circ}$, Ovoid tube: $65^{\circ}$) were used in the same condition. The differences between desired and actual source position were measured by using Image J. Results : In case of using 4 different angles of applicator with the straight universal applicator transfer tube, the average error was the lowest for $0^{\circ}$ applicator, greatest for $65^{\circ}$ applicator. However, All average errors were within ${\pm}2mm$ recommended in TG-56. When MultiSource container was moved 5 cm, 10 cm, 20 cm towards the EBT3 film, the average errors were beyond ${\pm}2mm$. The first dwell position was relatively located in accuracy, while the second and third dwells were displaced by an increasing magnitude with increasing curvature of the transfer tube. Furthermore, with increasing the angle of applicators, the error of all other dwell positioning was increased. Conclusion : The results of this study showed that both the curvature of universal applicator transfer tube and the angle of applicators affect the source dwell position. It is recommended that using straight universal applicator transfer tubes is followed in all cases, in order to avoid deviations in the delivered source dwell position. Also, It is advisable to verify the actual dwell position, using video camera quality control tool prior to all treatments.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.32 no.4_1
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• pp.299-309
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• 2014

This paper evaluated the possibility for 1/5,000 digital topographic mapping by using PLEIADES images of 0.5m GSD(Ground Sampling Distance) resolution that has recently launched. Those results of check points by applying the initial RPC(Rational Polynomial Coefficient) of PLEIADES images came out as; RMSE of those were $X={\pm}1.806m$, $Y={\pm}2.132m$, $Z={\pm}1.973m$. Also, if we corrected geometric correction using 16 GCP(Ground Control Point)s, the results of RMSE became $X={\pm}0.104m$, $Y={\pm}0.171m$, $Z={\pm}0.036m$, and t he RMSE of check points were $X={\pm}0.357m$, $Y={\pm}0.239m$, $Z={\pm}0.188m$; which of those results indicated the accuracy of standard adjustment complied in error tolerances of the 1/5,000 scale. Additionally, we converted coordinates of points, obtained by TerraSAR. for comparing with measurements from GPS(Global Positioning System) surveying. The RMSE of comparing converted and GPS points were $X={\pm}0.818m$, $Y={\pm}0.200m$, $Z={\pm}0.265m$, which confirmed the possibility for 1/5,000 digital topographic mapping with PLEIADES images and GCPs. As method of obtaining GCPs in unaccessible area, however, the outcome evaluation of GCPs extracted from TerraSAR images was not acceptable for 1/5,000 digital topographic mapping. Therefore, we considered that further researches are needed on applicability of GCPs extracted from TerraSAR images for future alternative method.