• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.402-403
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• 2018

70GHz-band high gain array antenna is developed for automotive short range radar sensor. In Short-rangeradar, the gain must be high in order to increase the resolution, and the angle width must be set to secure the field of view(Fov). The proposed antenna operates at 76~81GHz and satisfies angle width $60^{\circ}$, antenna gain 15dB and the input reflection coefficient of less than -10dB within the operating frequency. Wave guide WR-10 was used to measure the antenna and results similar to the simulation results were obtained.

• Journal of Electrical Engineering and Technology
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• v.7 no.3
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• pp.411-419
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• 2012

This paper proposes a new FDI(Fault Detection and Isolation) method, which is called EPSA(Extended Parity Space Approach). This method is particularly suitable for fault detection and isolation of the system with one faulty sensor or two faulty sensors. In the system with two faulty sensors, the fault detection and isolation probability may be decreased when two faults are occurred between the sensors related to the large fault direction angle. Nonetheless, the previously suggested FDI methods to treat the two-faults problem do not consider the effect of the large fault direction angle. In order to solve this problem, this paper analyzes the effect of the large fault direction angle and proposes how to increase the fault detection and isolation probability. For the increase the detection probability, this paper additionally considers the fault type that is not detected because of the cancellation of the fault biases by the large fault direction angle. Also for the increase the isolation probability, this paper suggests the additional isolation procedure in case of two-faults. EPSA helps that the user can know the exact fault situation. The proposed FDI method is verified through Monte Carlo simulation.

• Journal of Electrical Engineering and Technology
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• v.8 no.4
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• pp.899-910
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• 2013

This paper presents a novel lateral stability control system for electric vehicle based on sideslip angle estimation through Kalman filter using the integration of a single antenna GPS receiver and yaw rate sensor. Using multi-rate measurements including yaw rate and course angle, time-varying parameters disappear from the measurement equation of the proposed Kalman filter. Accurate sideslip angle estimation is achieved by treating the combination of model uncertainties and external disturbances as extended states. Active front steering and direct yaw moment are integrated to manipulate sideslip angle and yaw rate of the vehicle. Instead of decoupling control design method, a new control scheme, "two-input two-output controller", is proposed. The extended states are utilized for disturbance rejection that improves the robustness of lateral stability control system. The effectiveness of the proposed methods is verified by computer simulations and experiments.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.1 s.94
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• pp.253-264
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• 1999

Most autonomous mobile robots view only things in front of them, and as a result, they may collide with objects moving from the side or behind. To overcome this problem. an Active Omni-directional Range Sensor System has been built that can obtain an omni-directional range data through the use of a laser conic plane and a conic mirror. Also, mobile robot has to know its current location and heading angle by itself as accurately as possible to successfully navigate in real environments. To achieve this capability, we propose a self-localization algorithm of a mobile robot using an active omni-directional range sensor in an unknown environment. The proposed algorithm estimates the current position and head angle of a mobile robot by a registration of the range data obtained at two positions, current and previous. To show the effectiveness of the proposed algorithm, a series of simulations was conducted and the results show that the proposed algorithm is very efficient, and can be utilized for self-localization of a mobile robot in an unknown environment.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.2
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• pp.106-112
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• 2006

A new model for the continuous-magnetic interferences has been proposed in this paper to remove external interferes of magnetic field to the dual electric compass. By this removal, the dual electric compass can be used for proving the azimuth angle in an automobile navigation system instead of the rate gyroscope. In the navigation system with a GPS receiver, a DR sensor such as a rate gyroscope is needed to overcome the shielded areas, which is relatively expensive and requires frequent calibrations. However the dual electric compass designed by this research is cheap and provides absolute azimuth angle precisely, which is beneficiary to be used as a DR sensor. The main contribution of this paper is that the long-lasting magnetic interferences have been removed out by using the proposed model, which never be studied before. With a hybrid navigation system using a DR sensor, we demonstrated that dual electric compass is better than a rate gyroscope in terms of both economics and performances.

• Journal of Ocean Engineering and Technology
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• v.19 no.2 s.63
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• pp.82-89
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• 2005

This study deals with the development of the extended Kalman filter(EKF) algorithm for the localization of underwater mining vehicles. Both simulation and experimental studies in a test bed are carried out. For the experiments, a scale dawn tracked vehicle is run in a soil bin containing cohesive soil of bentonite-water mixture. To develop the EKF algorithm, we use a kinematic model including the inner/outer track slips and the slip angle for the vehicle. The measurements include the inner and outer wheel speeds from encoders, the heading angle from a compass sensor and a fiber optic rate gyro, and x and y coordinate position values from a vision system. The vision sensor replaces the LBL(Long Base Line) sonar system used in the real underwater positioning situations. Artificial noise signals mimicking the real LBL noise signal are added to the vision sensor information. To know the mean slip values of the tracks in both straight and cornering maneuver, several trial running experiments are executed before applying the EKF algorithm. Experimental results show the effectiveness of the EKF algorithm in rejecting the sensor measurements noise. Also, the simulation and experimental results show close correlations.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.1
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• pp.248-254
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• 2013

In location finding system using spaced multi-sensor, there is the phenomenon that the position estimation accuracy is degraded by the location of signal sources and the sensors. This phenomenon is called GDOP(Geometric Dilution Of Precision) effect. and to minimize these effects, research is needed on how. In this paper, I will describe how to minimize GDOP effect, estimating possibility of GDOP using AOA(angle of arrival) information of spaced multi sensors, and removing sensor error factor in position estimation.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.6
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• pp.229-235
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• 2018

Research on indoor location tracking technology using smart phone is actively being carried out. Especially, in order to display the movement path of the smartphone on the map, the azimuth angle should be estimated by using the geomagnetic sensor built in most smart phones. Due to the distortion of the magnetic field due to the surrounding steel structure and the inclination of the smartphone, the estimation error of azimuthal angle may be occurred. In this paper, we propose a correction method of the geomagnetic sensor at the stationary state and a correction method for the inclination of the smartphone. We also propose a method to correct the azimuth error due to the difference between the magnetic north and the grid north.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.6
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• pp.546-551
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• 2011

Tilt sensor is required to control the attitude of the biped robot when it walks on an uneven terrain. Vision sensor, which is used for recognizing human or detecting obstacles, can be used as a tilt angle sensor by comparing current image and reference image. However, vision sensor alone has a lot of technological limitations to control biped robot such as low sampling frequency and estimation time delay. In order to verify limitations of vision sensor, experimental setup of an inverted pendulum, which represents pitch motion of the walking or running robot, is used and it is proved that only vision sensor cannot control an inverted pendulum mainly because of the time delay. In this paper, to overcome limitations of vision sensor, Kalman filter for the multi-rate sensor fusion algorithm is applied with low-quality gyro sensor. It solves limitations of the vision sensor as well as eliminates drift of gyro sensor. Through the experiment of an inverted pendulum control, it is found that the tilt estimation performance of fusion sensor is greatly improved enough to control the attitude of an inverted pendulum.

• Proceedings of the KIPE Conference
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• 2001.10a
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• pp.768-772
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• 2001

The paper deals with the control of the synchronous reluctance machine without position sensor. A method for the computation of the transformation angle out of terminal voltages and currents is presented. The injection of test signals allows operation at zero speed. Fundamental for this control scheme is the exact modelling of the machine, where especially the saturable inductances are of central interest. The accuracy of the angle estimation method over the whole operating range including field-weakening is discussed in detail. The implementation of the angle estimation method in a rotor-oriented control scheme and practical results are demonstrated.