• Proceedings of the Korea Water Resources Association Conference
• /
• 2021.06a
• /
• pp.392-392
• /
• 2021

자료동화(data assimilation) 기법은 관측 자료와 예측 모형의 정보를 동시에 활용, 모형의 상태량(state variables)이나 매개변수(model parameters)를 실시간으로 업데이트하는 Bayesian 필터링 이론에 근거한 방법으로, 최근 이를 활용한 수문 모의 정확도 향상 기술이 빠르게 발전하고 있다. 본 연구에서는 앙상블 자료동화의 정확성을 향상시키기 위한 세부 방법인 along-the-stream localization과 inflation 기법의 분포형 수문 모형에 대한 적용성을 대규모 지역 단위(regional-scale) 모의를 통해 검토한다. 분포형 수문모형과 자료동화 framework로는 WRF-Hydro(Weather Research and Forecasting Model Hydrological Modeling System)와 DART(Data Assimilation Research Testbed)를 각각 적용한다. WRF-Hydro는 미국의 전 대륙지역(CONUS; continental United States)에 대한 수문 모델링 framework인 National Water Model의 핵심엔진이고, DART는 미국 National Center for Atmospheric Research(NCAR) 연구소에서 개발한 범용 자료동화 도구이다. 본 연구에서는 지표수 수문모형의 자료동화를 위해 개발된 기법인 along-the-stream localization과 inflation 기법이 하도 추적에 미치는 영향을 분석한다. along-the stream localization 기법은 공간적 근접도 외에 하도의 수문학적 연관관계를 고려하는 localization 기법으로, 상대적으로 수문학적 상관도가 떨어지는 하도에 대한 과도한 자료동화를 줄여줄 수 있다. inflation 기법은 앙상블의 다양성을 증가시키는 기법으로, 칼만 필터(Kalman filter)에 의한 업데이트의 이전이나 이후 적용하여 앙상블 예측의 정확도를 추가적으로 향상시킬 수 있다. 본 고에서는 앙상블 자료동화 기법을 지표수 수문 모의에 적용할 경우 남아 있는 난제와 적용 가능한 방법에 대해 중점적으로 논의한다.

• Journal of Advanced Navigation Technology
• /
• v.28 no.3
• /
• pp.262-271
• /
• 2024

In this paper, by applying deep learning, one of the A.I. techniques, through angle information, which is optical observation data generated when observing satellites at observatories, distance information from observatories is learned to predict range data, thereby increasing the precision of satellite's orbit determination. To this end, we generated observational data from GMAT, reduced the learning data error of deep learning through preprocessing of the generated observational data, and conducted deep learning through MATLAB. Based on the predicted distance information from learning, trajectory determination was performed using an extended Kalman filter, one of the filtering techniques for trajectory determination, through GMAT. The reliability of the model was verified by comparing and analyzing the orbital determination with angular information without distance information and the orbital determination result with predicted distance information from the model.

• Geophysics and Geophysical Exploration
• /
• v.25 no.4
• /
• pp.167-176
• /
• 2022

We designed a borehole deviation survey tool applicable for steel-cased holes, K-DEV, and developed a prototype for a depth of 500 m aiming to development of own equipment required to secure deep subsurface characterization technologies. K-DEV is equipped with sensors that provide digital output with verified high performance; moreover, it is also compatible with logging winch systems used in Korea. The K-DEV prototype has a nonmagnetic stainless steel housing with an outer diameter of 48.3 mm, which has been tested in the laboratory for water resistance up to 20 MPa and for durability by running into a 1-km deep borehole. We confirmed the operational stability and data repeatability of the prototype by constantly logging up and down to the depth of 600 m. A high-precision micro-electro-mechanical system (MEMS) gyroscope was used for the K-DEV prototype as the gyro sensor, which is crucial for azimuth determination in cased holes. Additionally, we devised an accurate trajectory survey algorithm by employing Unscented Kalman filtering and data fusion for optimization. The borehole test with K-DEV and a commercial logging tool produced sufficiently similar results. Furthermore, the issue of error accumulation due to drift over time of the MEMS gyro was successfully overcome by compensating with stationary measurements for the same attitude at the wellhead before and after logging, as demonstrated by the nearly identical result to the open hole. We believe that the methodology of K-DEV development and operational stability, as well as the data reliability of the prototype, were confirmed through these test applications.

• Proceedings of the International Union of Geodesy And Geophysics Korea Journal of Geophysical Research Conference
• /
• 2003.05a
• /
• pp.19-19
• /
• 2003

본 연구에서는 국립해양조사원의 '해양2000호'를 통해 1996년과 1997년에 측정한 동해 지역의 중력자료에 대한 자료 처리를 하였다. 효과적인 자료처리를 위해 선상중력자료 처리에 필요한 각종 보정 절차와 문제점 등을 알아보았으며, 선상자료와 해면고도계자료의 비교 및 이를 통한 선상자료의 검증을 실시하였다. 선상중력자료는 측정과 처리 과정에 있어 여러 사항을 고려하여야 한다. 즉, 육상중력기점을 이용한 절대중력으로의 환산 문제, 선박 항해 위치의 부정확성에 기인하는 문제 및 중력계의 기계적 특성과 중력 측정이 이루어질 때의 해상 조건에 의한 영향 등으로 선상중력자료에 나타나는 여러 오차를 최소화하여야 한다. 선상중력자료로부터 각종 지구중력장 연구에 필요한 중력이상을 계산하기 위해 선상중력 측정시 기인되는 각종 요인의 오차를 고려한 효과적인 보정이 이루어져야 한다. 즉, 선상중력계의 기계변이 보정, 탐사선에 대한 위치 자료의 획득 및 필터링, 그리고 탐사선의 이동으로 인한 Eotvos 효과의 정확한 계산 및 보정이 필요하고, 선상중력계의 기계적 특성에 의해 나타나는 시간지연에 대한 보정도 필요하다. 또한 이러한 보정을 통해 계산한 중력 이상에서 각 교점의 오차를 보정하는 교정오차 보정도 실시하여야 한다. 특히, 탐사선의 이동으로 인한 지구자전 각속도의 상대적인 증감의 효과로 나타나는 Eotvos 효과의 영향은 선상중력자료의 정확도에 가장 큰 영향을 미친다. 이의 정확한 계산 및 보정을 위해서는 정확한 위치정보가 필요하며 본 연구에서는 이를 위해 GPS 항해정보에 대한 Kalman 필터를 실시하였고, Eotvos 효과에 대해 Savitzky-Golay 필터를 적용하여 최적의 Eotvos 보정을 시도하였다. 본 연구에서 계산된 동해지역의 중력이상에 대한 대력적인 범위는 경도 129° - 133°이고 위도 35° - 38.3° 부근이다. 이 지역에 대한 고도이상은 최소 -42.46 mGal에서 최고 161.13 mGal사이에 분포하며, 고도이상의 평균은 14.450 mGal이다. 또한 Bouguer 이상은 최소 -l5.09 mGal에서 최고 218.61 mGal이고 이의 평균은 82.681 mGal이다. 그리고 동해지역의 선상중력 측정지역에서 선상자료에 의한 중력이상과 Altimeter 자료에 의한 고도이상의 전반적인 윤곽은 비슷하면서도 일부 작은 이상의 차이가 나타났으며, 지형자료와 비교하여 보면 Altimeter에 의한 결과보다 선상측정에 의한 결과가 더욱 잘 일치하고 있어 본 연구에서 계산한 선상자료의 타당성을 알 수 있다. 고도이상의 차이는 최소 -25.94 mGal에서 최대 85.33 mGal의 차이를 보이며 차이의 평균은 3.517 mGal, RMS는 6.774 meal이다. 이는 비교적 큰 차이로 선상측정자료의 중요성과 필요성을 단적으로 나타내고 있다.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.37 no.4
• /
• pp.447-459
• /
• 2013

Many problems need to be solved before vision systems can actually be applied in industry, such as the precision of the kinematics model of the robot control algorithm based on visual information, active compensation of the camera's focal length and orientation during the movement of the robot, and understanding the mapping of the physical 3-D space into 2-D camera coordinates. An algorithm is proposed to enable robot to move actively even if the relative positions between the camera and the robot is unknown. To solve the correction problem, this study proposes vision system model with six camera parameters. To develop the robot vision control algorithm, the N-R and EKF methods are applied to the vision system model. Finally, the position accuracy and processing time of the two algorithms developed based based on the EKF and the N-R methods are compared experimentally by making the robot perform slender bar placement task.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• v.9 no.2
• /
• pp.168-172
• /
• 2005

An autopilot system of a ship is very important for a safe and convenient navigation, which is realized with getting an azimuth data from a gyrocompass, a magnetic compass and a GPS(Global Positioning System) compass. Magnetic compass an azimuth error is generated by a vessel magnetism material such as steels. The magnetic pole is detected by the magnetic field sensor, it does not coincide with the true north, therefore, the detected azimuth data can not but accompany error. In this paper, in order to detect the minimum change of azimuth data which generates errors of azimuth information, a search algorithm using the Kalman Filtering method is utilized. The digital electronic compass is designed with the integration algorithm using the merits of an earth's magnetic field sensor and a GPS receiver.

• Journal of the Korean Institute of Telematics and Electronics S
• /
• v.36S no.1
• /
• pp.51-59
• /
• 1999

In this paper we propose the technique for tracking players and a ball and for obtaining players' ground traces using image mosaic in general soccer sequences. Here, general soccer sequences mean the case that there is no extreme zoom-in or zoom-out of TV camera. Obtaining player's ground traces requires that the following three main problems be solved. There main problems: (1) ground field extraction (2) player and ball tracking and team indentification (3) player positioning. The region of ground field is extracted on the basis of color information. Players are tracked by template matching and Kalman filtering. Occlusion reasoning between overlapped players in done by color histogram back-projection. To find the location of a player, a ground model is constructed and transformation between the input images and the field model is computed using four or more feature points. But, when feature points extracted are insufficient, image-based mosaic technique is applied. By this image-to-model transformation, the traces of players on the ground model can be determined. We tested our method on real TV soccer sequence and the experimental results are given.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.25 no.5
• /
• pp.444-450
• /
• 2015

The accuracy of small and low cost CCD camera is insufficient to provide data for precisely tracking unmanned aerial vehicles(UAVs). This study shows how UAV can hover on a human targeted tracking object by using CCD camera rather than imprecise GPS data. To realize this, UAVs need to recognize their attitude and position in known environment as well as unknown environment. Moreover, it is necessary for their localization to occur naturally. It is desirable for an UAV to estimate of his attitude by environment recognition for UAV hovering, as one of the best important problems. In this paper, we describe a method for the attitude of an UAV using image information of a maker on the floor. This method combines the observed position from GPS sensors and the estimated attitude from the images captured by a fixed camera to estimate an UAV. Using the a priori known path of an UAV in the world coordinates and a perspective camera model, we derive the geometric constraint equations which represent the relation between image frame coordinates for a marker on the floor and the estimated UAV's attitude. Since the equations are based on the estimated position, the measurement error may exist all the time. The proposed method utilizes the error between the observed and estimated image coordinates to localize the UAV. The Kalman filter scheme is applied for this method. its performance is verified by the image processing results and the experiment.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.16 no.6
• /
• pp.90-100
• /
• 2017

The purpose of this study is to detect and label the vehicles using the drone images as a way to overcome the limitation of the existing point and section detection system and vehicle gap estimation on Arterial road. In order to select the appropriate time zone, position, and altitude for the acquisition of the drone image data, the final image data was acquired by shooting under various conditions. The vehicle was detected by applying mixed Gaussian, image binarization and morphology among various image analysis techniques, and the vehicle was labeled by applying Kalman filter. As a result of the labeling rate analysis, it was confirmed that the vehicle labeling rate is 65% by detecting 185 out of 285 vehicles. The gap was calculated by pixel unitization, and the results were verified through comparison and analysis with Daum maps. As a result, the gap error was less than 5m and the mean error was 1.67m with the preceding vehicle and 1.1m with the following vehicle. The gaps estimated in this study can be used as the density of the urban roads and the criteria for judging the service level.

• Journal of Navigation and Port Research
• /
• v.37 no.6
• /
• pp.575-580
• /
• 2013

The IMU(Inertial Measurement Unit) which is the expensive equipment has been used as a special limited area, usually in measurement of posture of applying to the areas of ship, submarine, aircraft and military equipment application. However, in the current situation, MEMS AHRS technology can replace the high-priced IMU in MEMS AHRS selected application field. In this paper, wireless hull motion measurement system was suggested for measuring key elements of ship's movement such as rolling, pitching and yawing using gyro, acceleration and magnetic sensors of AHRS. In order to reduce the error such as instantaneous acceleration, effects and vibration of geomagnetic, we have adopted the sensors equipped with Kalman filtering. The Wireless hull motion measurement system using AHRS sensors was tested in actual ship and it could easily be applied in limited installation circumstances of the ship. In the future, this system can be useful in the navigation safety and marine accident analysis by using with ship equipment such as INS or VDR in the maritime.