• Transactions of the Korean Society of Automotive Engineers
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• v.24 no.4
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• pp.408-415
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• 2016

The vehicle attitude and sideslip is critical information to control the vehicle to prevent from unintended motion. Many of estimation strategy use bicycle model or IMU integration, but both of them have limits on application. The main purpose of this paper is development of vehicle orientation estimator which is robust to various vehicle state and road shape. The suggested estimator use 3-axis magnetometer, yaw rate sensor and lateral acceleration sensor to estimate three Euler angles of vehicle. The estimator is composed of two individual observers: First, comparing the known magnetic field and gravity with measured value, the TRIAD algorithm calculates optimal rotational matrix when vehicle is in static or quasi-static condition. Next, merging 3-axis magnetometer with inertial sensors, the extended Kalman filter is used to estimate vehicle orientation under dynamic condition. A validation through simulation tools, Carsim and Simulink, is performed and the results show the feasibility of the suggested estimation method.

• Proceedings of the Korea Information Processing Society Conference
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• 2003.11c
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• pp.1383-1386
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• 2003

최근 공간 데이터베이스의 선택률 추정 문제에 대한 관심이 증가하면서, 데이터분포의 편중, 중복 계산, 메모리 공간 최소화등의 문제를 고려한 다양한 기법들이 제안되고 있다. 그러나 이들 기법들 간의 성능 분석을 통한 비교평가는 이루어지지 않고 있다. 따라서, 이 논문에서는 공간 영역 객체의 범위질의에 관한 선택률 추정 기법인 Min-Skew, 웨이블릿, 누적밀도, 오일러 히스토그램을 비교 분석한다. 즉, 실제 데이터셋을 기반으로 여러 형태의 질의에 대한 성능 비교를 통해 각 기법들을 비교 평가한다. 이 연구 결과는 새로운 기법 도출에 이용될 수 있다.

• Journal of Convergence for Information Technology
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• v.7 no.5
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• pp.137-148
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• 2017

Recently, researchers are actively addressed to utilize Unmanned Aerial Vehicles(UAV) for military and industry applications. One of these applications is to trace the preceding flight when it is necessary to track the route of the suspicious reconnaissance aircraft in secret, and it is necessary to estimate the attitude of the target flight such as Roll, Yaw, and Pitch angles in each instant. In this paper, we propose a method for estimating in real time the attitude of a target aircraft using the video information that is provide by an external camera of a following aircraft. Various image processing methods such as color space division, template matching, and statistical methods such as linear regression were applied to detect and estimate key points and Euler angles. As a result of comparing the X-plane flight data with the estimated flight data through the simulation experiment, it is shown that the proposed method can be an effective method to estimate the flight attitude information of the previous flight.

• Journal of Korea Multimedia Society
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• v.12 no.9
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• pp.1217-1232
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• 2009

In this paper, we propose a semi-automatic 3D building reconstruction method using uncalibrated images which includes the facade of target building. First, we extract feature points in all images and find corresponding points between each pair of images. Second, we extract lines on each image and estimate the vanishing points. Extracted lines are grouped with respect to their corresponding vanishing points. The adjacency graph is used to organize the image sequence based on the number of corresponding points between image pairs and camera calibration is performed. The initial solid model can be generated by some user interactions using grouped lines and camera pose information. From initial solid model, a detailed building model is reconstructed by a combination of predefined basic Euler operators on half-edge data structure. Automatically computed geometric information is visualized to help user's interaction during the detail modeling process. The proposed system allow the user to get a 3D building model with less user interaction by augmenting various automatically generated geometric information.

• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.4
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• pp.469-475
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• 2015

This paper describes about the method for designing an extended Kalman filter to accurately measure the position of the spatial-phase system using a semiconductor sensor. Spatial position is expressed by the correlation of the rotated coordinate system attached to the body from the inertia coordinate system (a fixed coordinate system). To express the attitude, quaternion was adapted as a state variable, Then, the state changes were estimated from the input value which was measured in the gyro sensor. The observed data is the value obtained from the acceleration sensor. By matching between the measured value in the acceleration sensor and the predicted calculation value, the best variable was obtained. To increase the accuracy of estimation, designation of the extended Kalman filter was performed, which showed excellent ability to adjust the estimation period relative to the sensor property. As a result, when a three-axis gyro sensor and a three-axis acceleration sensor were adapted in the estimator, the RMS(Root Mean Square) estimation error in simulation was retained less than 1.7[$^{\circ}$], and the estimator displayed good property on the prediction of the state in 100 ms measurement period.