• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.158-163
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• 2009

In recent years, there has been increased interest in characterizing and extracting 3D information from 2D images for human tracking and identification. In this paper, we propose a single view-based framework for robust estimation of height and position. In the proposed method, 2D features of target object is back-projected into the 3D scene space where its coordinate system is given by a rectangular marker. Then the position and the height are estimated in the 3D space. In addition, geometric error caused by inaccurate projective mapping is corrected by using geometric constraints provided by the marker. The accuracy and the robustness of our technique are verified on the experimental results of several real video sequences from outdoor environments.

• Journal of Power Electronics
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• v.11 no.6
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• pp.856-863
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• 2011

In this paper a novel method of the Ant Colony Optimization algorithm for rotor position estimation in Switched Reluctance Motors is presented. The data provided by the initial assumptions is one of the important aspects used to solve the problems relative to an Ant Colony algorithm. Considering the nature of a real ant colony, it was found that the ants have no primary data for deducing which is the shortest path in their initial iteration. They also do not have the ability to see the food sources at a distance. According to this point of view, a novel method is presented in which the rotor pole position relative to the corresponding stator pole in a switched reluctance motor is estimated with high accuracy using the active and inactive phase parameters. This new method gives acceptable results such as a desirable convergence together with an optimized and stable response. To the best knowledge of the authors, such an analysis has not been carried out previously.

• Journal of Positioning, Navigation, and Timing
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• v.6 no.3
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• pp.117-123
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• 2017

In this paper, we propose a performance index that can compare the position estimation performance according to the time slot allocation order, which is superior in the position estimation performance in the operation of the Link-16 based relative navigation system. In order to verify the validity of the performance index, a software-based Link-16 relative navigation system performance analysis platform composed of a signal generator, a signal reception and navigation algorithm execution unit, and a performance analysis unit was designed. Using the designed software platform, we analyzed the relationship between proposed performance index and position estimation performance according to time slot allocation order in the same position reference (PR) arrangement. The performance index of the proposed time slot allocation is expected to be utilized not only for the Link-16 system, but also for the Time Division Multiple Access (TDMA)-based navigation system.

• Journal of the Korea Institute of Military Science and Technology
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• v.17 no.4
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• pp.422-429
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• 2014

Proximity sensor networks are aimed at estimation kinematic state of target using estimated position of the target by each sensor node or target parameter. To analyze the kinematic state of target, traditional approaches require detections on multiple sensors, very large number of sensors to achieve acceptable performance. In this paper, we propose a novel method which can estimate predicted position of the underwater target using minimum proximity sensor with bearing information to this problem. The proposed algorithm was verified performance through simulation.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2012.10a
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• pp.261-262
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• 2012

In this research, intelligent protection system for laser boat is introduced. The function of system is to measure the distance and velocity of object from our boat and generate control signals to avoid collision with moving targets. A novel approach to estimate object's position from our ship is tackled on this paper. To do this laser sensors are used to measure distance from ship to targets. The ship position and velocity is estimated by th Kalman filter algorithm. In the real phase, the filtering method will be applied to process signal gathered by laser sensors. Simulation to estimate ship's position and velocity under noise are executed and the results are introduced to show the effectiveness of the algorithm.

• ETRI Journal
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• v.37 no.4
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• pp.766-771
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• 2015

Robust motion estimation for human-computer interactions played an important role in a novel method of interaction with electronic devices. Existing pose estimation using a monocular camera employs either ego-motion or exo-motion, both of which are not sufficiently accurate for estimating fine motion due to the motion ambiguity of rotation and translation. This paper presents a hybrid vision-based pose estimation method for fine-motion estimation that is specifically capable of extracting human body motion accurately. The method uses an ego-camera attached to a point of interest and exo-cameras located in the immediate surroundings of the point of interest. The exo-cameras can easily track the exact position of the point of interest by triangulation. Once the position is given, the ego-camera can accurately obtain the point of interest's orientation. In this way, any ambiguity between rotation and translation is eliminated and the exact motion of a target point (that is, ego-camera) can then be obtained. The proposed method is expected to provide a practical solution for robustly estimating fine motion in a non-contact manner, such as in interactive games that are designed for special purposes (for example, remote rehabilitation care systems).

• Proceedings of the KSR Conference
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• 2011.10a
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• pp.226-231
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• 2011

This research was done to prove the optimal position to detect a train reader when using a multiple fusion sensor. The experiment was done using four Train installed RFID Readers located on the train. These readers were read by sensors installed at intervals of 50 meters on the up and down sections of the Line 8, from Amsa station to Moran station. We analyze errors in the recognition range according to the Tag's number of recognition due to RFID of train speed, and propose a method of estimation for an accurate estimation of the position of train At this the Least-Squares Method is applied to judge the position of train accurately from the error because of Tag's number of recognition and RFID of train speed. also It is verified through simulation.

• Journal of Power Electronics
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• v.14 no.6
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• pp.1243-1253
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• 2014

The phase inductance of a switch reluctance motor (SRM) is significantly nonlinear. With different saturation conditions, the phase inductance shape is clearly changed. This study focuses on the relationship between coefficient and current in an inductance model with ignored harmonics above the order of 3. A position estimation method based on the variable coefficient inductance model is proposed in this paper. A four-quadrant sensorless control system of the SRM drive is constructed based on the relationship between variable coefficient inductance and rotor position. The proposed algorithms are implemented in an experimental SRM test setup. Experimental results show that the proposed method estimates position accurately in operating two/four-quadrants. The entire system also has good static and dynamic performance.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.187-189
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• 2009

Position estimation in indoor is significant problem, because GPS which is usually used for outdoor positioning cannot be utilized to indoor positioning. Sensor network can be a solution for the positioning. Recently, chirp spread spectrum(CSS) specified in IEEE 802.15.4a provides an ability of ranging. Based on the results of the ranging, a position of a CSS node can be calculated by using trilateration. In this case, Kalman filter can be applied to the trilateration because of the measurement noise. In this paper, we apply the unscented Kalman filter for the trilateration. The trilateration can be represented to a nonlinear state space equation, and the unscented Kalman filter is suitable for nonlinear state space equation. Through the experimental results. we show the accuracy of the estimated position.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.1121-1124
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• 1999

Linear motor is able to produce line movement without rotary-to-line converter at the system required line moving. Thus Linear motor has no gear, screw, belt for line movement. Therefore it has some advantage which decrease friction loss, noise, vibration, maintenance effort and prevent decay of control performance due to backlash. This paper proposes the estimation method of unknown parameters from the BLDC Linear motor and determine the PI controller gain through this estimation. Each control movement that is current, speed, position control, and PWM wave generation is performed on Processor, which is DSP(Digital Signal Processor), having high speed performance. PI theory is adopted to each for controller for control behavior More fast convergence to command position is accomplished by applying the new velocity locus which derived from position error.