• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1259-1261
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• 2003

The vehicle's heading angle determination is formulated and the proposed method based on geometry engages the magnetometer and the GPS. The resulting maximum determination accuracy of 0.3deg over the entire earth as a standard deviation is obtained for a magnetometer with measurement error of 1nT.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2004.04a
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• pp.59-64
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• 2004

In this paper, the error compensation method of the low-cost IMU is proposed. In general, the position and attitude error calculated by accelerometers and gyros grows with time. Therefore the additional information is required to compensate the drift. The attitude angles can be bound accelerometer mixing algorithm and the heading angle can be aided by single antenna GPS velocity. The Kalman filter is used for error compensation. The result is verified by comparing with the attitude calculated by Attitude Heading Reference System with Micro Electro Mechanical System for a basis

• Journal of Navigation and Port Research
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• v.37 no.4
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• pp.329-335
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• 2013

This paper is to develop the position error equations including the attitude errors, the errors of nadir and ship's heading, and the errors of ship's position in the free-gyro positioning and directional system. In doing so, the determination of ship's position by two free gyro vectors was discussed and the algorithmic design of the free-gyro positioning and directional system was introduced briefly. Next, the errors of transformation matrices of the gyro and body frames, i.e. attitude errors, were examined and the attitude equations were also derived. The perturbations of the errors of the nadir angle including ship's heading were investigated in each stage from the sensor of rate of motion of the spin axis to the nadir angle obtained. Finally, the perturbation error equations of ship's position used the nadir angles were derived in the form of a linear error model and the concept of FDOP was also suggested by using covariance of position error.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2004.11a
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• pp.117-121
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• 2004

In this paper, the error compensation method of the low-cost IMU is proposed. In general, the position and attitude error calculated by accelerometers and gyros grows with time. Therefore the additional information is required to compensate the drift. The attitude angles can be bound accelerometer mixing algorithm and the heading angle can be aided by single antenna GPS velocity. The Kalman filter is used for error compensation. The result is verified by comparing with the attitude calculated and dynamics position determination by Attitude Heading Reference System with Micro Electro Mechanical System for a basis

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.2
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• pp.118-124
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• 2008

Recently fishing industry is interested in efficiency and automation to acquire the international competitive power of national fishing industry. As an automation device of fishing boat, there are electric compasses using GPS and terrestrial magnetic sensor. Electric compass can be minimum size, high effectiveness with keeping the characteristic of a magnetic compass. This can be used a heading angle sensor to construct auto-navigation system in a small size ship. This paper develop electronic compass system that has serial output signal in NMEA 0183 and demonstrates the possibility of the electronics compass in navigation system for a small sized ship.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.3
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• pp.210-216
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• 2015

This paper proposes a method to determine vehicle driving state using the driving characteristics index. This index is a quantitative value to classify the driving state of a vehicle with its velocity and heading angle in that instant. It can classify driving state into straight driving, lane changing driving and curve driving in real time. In addition, the number of positional information is movably set up by designed region of interest. The proposed index is expressed on the stable driving states. Each driving state has characteristic tendency, and is compared with index distributional areas. The proposed method is verified by the actual driving experiment on the KATECH proving ground.

• Journal of the Korean Geophysical Society
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• v.9 no.4
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• pp.361-369
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• 2006

This study conducted an initialization test to decide dynamic position using AHRS IMU sensor, and derived attitude correction angles of vehicles against time through regression analysis. It was also found that the heading angle was stabilized with variation less than 1°after 60 seconds. Using these angles, this study carried out an experiment on the determination of dynamic position for each system in the open sky and in a semi-open sky. According to the results, in the open sky, DGPS alone systems were excellent in accuracy but poor in data acquisition, so the moving distance was around 12m. In DGPS/IMU combined system, accuracy and data acquisition were satisfactory and the moving distance was around 0.3m. In a semi-open sky, DGPS alone systems were excellent in accuracy in order of DGPS < FIMU < DGPS/IMU according to average and standard errors obtained with exclusion of places where data were not be obtained. The moving distance was the same as that in the open sky. For DGPS, when places where data were not obtainable were divided into Several block and they were compared, the maximum deviation from the trajectory was up to 41.5m in DGPS alone system, but it was less than 2.2m and average and standard errors were significantly improved in the combined system. When the navigation system was applied to surveys and the result was compared with position error 0.2mm under the guideline for digital map, it was possible to work on maps on a scale of up to 1 : 1,000.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.30 no.7
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• pp.51-60
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• 2002

The Monte-Carlo simulation of statistical analysis is used to investigate the final conditions of states as well as the footprint boundaries resulting from the atmospheric re-entry dispersions. The re-entry dispersions in this paper are specified by a $7\times7$ covariance matrix of latitude, longitude, altitude, bank angle, flight path angle, heading error, and range at entry velocity. The error sources that affect these at re-entry for a deboost are the uncertainties associated with atmospheric density and temperature, initial errors, wind, and estimation error of aerodynamic coefficients. Using $3{\sigma}_n$ deviations of these errors and a nominal flight trajectory, the covariance matrix of state variables can be determined by performing a trajectory error analysis. Major considerations in the application of the Monte-Carlo method are the simulation of perturbed trajectories, bank reversal, and determination of the impact points for each of these trajectories. This paper analyzes the results of uncertainties from the viewpoint of aero-coefficients and bank reversal.