• Journal of the Institute of Electronics Engineers of Korea SC
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• v.41 no.1
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• pp.1-8
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• 2004

The INS(Inertial Navigation System) provides high rate position, velocity and attitude data with good short-term stability while the GPS(Global Position System) provides position and velocity data with long-term stability. By integrating the INS with GPS, a navigation system can be achieved to Provide highly accurate navigation Performance. For the best performance, time synchronization of GPS and INS data is very important in GPS/INS integrated system But, it is impossible to synchronize them exactly due to the communication and computation time-delay. In this paper, to reduce the error caused by the measurement time-delay in GPS/INS integrated systems, error compensation methods using separate bias Kalman filter are suggested for both the loosely-coupled and the tightly-coupled GPS/INS integration systems. Linearized error models for the position and velocity matching GPS/INS integrated systems are Int derived by linearizing with respect to its time-delay and augmenting the delay-state into the conventional state equations for each case. And then separate bias Kalman Inter is introduced to estimate the time-delay during only initial navigation stage. The simulation results show that the present method is effective enough resulting in considerably less position error.

• Journal of the Korean Society of Marine Environment & Safety
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• v.19 no.6
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• pp.666-673
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• 2013

This paper proposes the performance evaluation test of attitude heading reference system (AHRS) suitable for small high speed autonomous underwater vehicle(AUV). Although IMU can provides the detail attitude information, it is sometime not suitable for small AUV with short operation time in view of price and the electrical power consumption. One of alternative for tactical grade IMU is the AHRS based micro-machined electro mechanical system(MEMS) which can overcome many problems that have inhibited the adoption of inertial system for small AUV such as cost and power consumption. A cost effective and small size AHRS which incorporates measurements from 3-axis MEMS gyroscopes, accelerometers, and 3-axis magnetometers has been developed to provide a complete attitude solution for AUV and the attitude calculation algorithm is derived based the coordinate transform equation and Kalman filter. The developed AHRS was validated through various performance tests as like the magnetometer calibration, operating experiments using land mobile vehicle and flight motion simulator (FMS). The test of magnetometer calibration shows the developed MEMS AHRS is robust to the external magent field change and the test with land vehicle proves the leveling error of developed MEMS AHRS is below $0.5^{\circ}/hr$. The results of FMS test shows the fact that AHRS provides the measurement with $0.5^{\circ}/hr$ error during 5 minutes operation time. These results of performance evaluation tests showed that the developed AHRS provides attitude information which error of roll and pitch are below $1^{\circ}$ and the error of yaw is below $5^{\circ}$ and satisfies the required specification. It is expected that developed AHRS can provide the precise attitude measurement under sea trial with real AUV.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.3
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• pp.352-361
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• 2021

An underwater positioning method that can be applied to structures for underwater construction is being developed at the Korea Institute of Ocean Science and Technology. The method uses an extended Kalman filter (EKF) based on an inertial navigation system for precise and continuous position estimation. The observation matrix was configured to be variable in order to apply asynchronous measured sensor data in the correction step of the EKF. A Doppler velocity logger (DVL) can acquire signals only when attached to the bottom of an underwater structure, and it is difficult to install and recover. Therefore, a complex sensor device for underwater structure attachment was developed without a DVL in consideration of an underwater construction environment, installation location, system operation convenience, etc.. Its performance was verified through a water tank test. The results are the measured underwater position using an ultra-short baseline, the estimated position using only a position vector, and the estimated position using position/velocity vectors. The results were compared and evaluated using the circular error probability (CEP). As a result, the CEP of the USBL alone was 0.02 m, the CEP of the position estimation with only the position vector corrected was 3.76 m, and the CEP of the position estimation with the position and velocity vectors corrected was 0.06 m. Through this research, it was confirmed that stable underwater positioning can be carried out using asynchronous sensors without a DVL.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.11
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• pp.1423-1433
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• 2018

Recently, a permanent magnet synchronous motor of middle and small-capacity has high torque, high precision control and acceleration / deceleration characteristics. But existing control has several problems that include unpredictable disturbances and parameter changes in the high accuracy and rigidity control industry or nonlinear dynamic characteristics not considered in the driving part. In addition, in the drive method for the control of low-vibration and high-precision, the process of connecting the permanent magnet synchronous motor and the load may cause the response characteristic of the system to become very unstable, to cause vibration, and to overload the system. In order to solve these problems, various studies such as adaptive control, optimal control, robust control and artificial neural network have been actively conducted. In this paper, an incremental encoder of the permanent magnet synchronous motor is used to detect the position of the rotor. And the position of the detected rotor is used for low vibration and high precision position control. As the controller, we propose augmented state feedback control with a speed observer and first order deadbeat disturbance observer. The augmented state feedback controller performs control that the position of the rotor reaches the reference position quickly and precisely. The addition of the speed observer to this augmented state feedback controller compensates for the drop in speed response characteristics by using the previously calculated speed value for the control. The first order deadbeat disturbance observer performs control to reduce the vibration of the motor by compensating for the vibrating component or disturbance that the mechanism has. Since the deadbeat disturbance observer has a characteristic of being vulnerable to noise, it is supplemented by moving average filter method to reduce the influence of the noise. Thus, the new controller with the first order deadbeat disturbance observer can perform more robustness and precise the position control for the influence of large inertial load and natural frequency. The simulation stability and efficiency has been obtained through C language and Matlab Simulink. In addition, the experiment of actual 2.5[kW] permanent magnet synchronous motor was verified.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.46 no.2
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• pp.84-91
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• 2009

This paper presents an online partial 3D modeling methodology that uses a mobile augmented reality system and aerial photographs, and a tracking methodology that compares the 3D model with a video image. Instead of relying on models which are created in advance, the system generates a 3D model for a real building on the fly by combining frontal and aerial views. A user's initial pose is estimated using an aerial photograph, which is retrieved from a database according to the user's GPS coordinates, and an inertial sensor which measures pitch. We detect edges of the rooftop based on Graph cut, and find edges and a corner of the bottom by minimizing the proposed cost function. To track the user's position and orientation in real-time, feature-based tracking is carried out based on salient points on the edges and the sides of a building the user is keeping in view. We implemented camera pose estimators using both a least squares estimator and an unscented Kalman filter (UKF). We evaluated the speed and accuracy of both approaches, and we demonstrated the usefulness of our computations as important building blocks for an Anywhere Augmentation scenario.

• 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.