• IE interfaces
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• v.23 no.3
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• pp.239-245
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• 2010

This paper considers a localization problem of a moving tag on RFID(Radio Frequency Identification) systems, where a positioning engine collects TDOA(Time-difference of Arrival) signal from a target tag to estimate the position of the tag. To localize the tag in the RFID system, we develop two heuristic algorithms and evaluate their performance in the estimation error and computational time by using randomly generated numerical examples. Based upon the performance evaluation, we can conclude our algorithms are valuable for localization the moving target.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.45 no.12
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• pp.97-104
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• 2008

Location-based services provide customized information or services according to the user's location. The existing localization schemes for outdoor environment are not applicable to the indoor localization system which requires higher accuracy of location estimation than that of the outdoor localization system. In this paper, we employ the received signal strength(RSS) to approximate the distance between a moving target and a reference point and use the triangulation method to estimate the location of the moving target for the indoor localization system in IEEE 802.15.4 wireless PAN(personal area network). For the indoor localization system, we propose a scheme which selects the best reference points to enhance the localization accuracy and adaptively reflects the changes in propagation environments of a moving target to the distance approximation. Through the implementation of the localization system, we have verified the performance of the proposed scheme in terms of the estimation accuracy.

• The KIPS Transactions:PartC
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• v.16C no.5
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• pp.645-652
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• 2009

Location-based service providing the customized information or service according to the user's location has attracted a lot of attention from the mobile communication industry. The service is realized by means of several building blocks, a localization scheme, service platform, application and service. The localization scheme figures out a moving target's position through measuring and processing a wireless signal. In this paper, we propose an adaptive localization scheme in an indoor localization system based on IEEE 802.15.4 standard. In order to enhance the localization accuracy, the proposed scheme selects the best reference points and adaptively reflects the changes of propagation environments of a moving target to approximate distances between the target and the reference points in RSS(Received Signal Strength) based localization system using triangulation. Through the implementation of the localization system, we verify the performance of the proposed scheme in terms of the localization accuracy.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.3
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• pp.445-450
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• 2015

In the moving target problem, the velocity information of the moving target is very important as well as the high accuracy position information. To solve this problem, active researches are being conducted recently with combine the Time Difference of Arrival (TDOA) and Frequency Delay of Arrival(FDOA) measurements. However, since the FDOA measurement is utilizing the Doppler effect due to the relative velocity between the target source and the receiver sensor, it may be difficult to use the FDOA measurement if the moving target speed is not sufficiently fast. In this paper, we propose a method for estimating the position and the velocities of the target by using only the TDOA measurements for the low speed moving target in the indoor environment with sensor network. First, the target position and heading angle are obtained from the estimated positions of two attached transmitters on the target. Then, the target angular and linear velocities are also estimated. In addtion, we apply the Instrumental Variable (IV) technique to compensate the estimation error of the estimated target velocity. In simulation, the performance of the proposed algorithm is verified.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.1
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• pp.7-13
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• 2015

Unmanned air vehicles (UAVs) are getting popular not only as a private usage for the aerial photograph but military usage for the surveillance, reconnaissance and supply missions. For an UAV to successfully achieve these kind of missions, geolocation (localization) must be implied to track an interested target or fly by reference. In this research, we adopted multi-sensor fusion (MSF) algorithm to increase the accuracy of the geolocation and verified the algorithm using two multicopter UAVs. One UAV is equipped with an optical camera, and another UAV is equipped with an optical camera and a laser range finder. Throughout the experiment, we have obtained measurements about a fixed ground target and estimated the target position by a series of coordinate transformations and sequential Kalman filter. The result showed that the MSF has better performance in estimating target location than the case of using single sensor. Moreover, the experimental result implied that multi-sensor geolocation algorithm is able to have further improvements in localization accuracy and feasibility of other complicated applications such as moving target tracking and multiple target tracking.

• The Journal of the Acoustical Society of Korea
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• v.26 no.4
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• pp.173-181
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• 2007

In this paper, we propose a moving target localization algorithm using acoustic spectrograms. A time-versus-frequency spectrogram provide a information of trajectory of the moving target in underwater. For a source at sufficiently long range from a receiver, broadband striation patterns seen in spectrogram represents the mutual interference between modes which reflected by surface and bottom. The slope of the maximum intensity striation is influenced by waveguide invariant parameter ${\beta}$ and distance between target and sensor. When more than two sensors are applied to measure the moving ship-radited noise, the slope and frequency of the maximum intensity striation are depend on distance between target and receiver. We assumed two sensors to fixed point then form a circle of apollonios which set of all points whose distances from two fixed points are in a constant ratio. In case of three sensors are applied, two circle form an intersection point so coordinates of this point can be estimated as a position of target. To evaluates a performance of the proposed localization algorithm, simulation is performed using acoustic propagation program.

• KIISE Transactions on Computing Practices
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• v.23 no.4
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• pp.210-216
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• 2017

In the paper we propose and implement a new indoor localization system where the techniques of magnetic field based fingerprinting and pedestrian dead reckoning are combined. First, we determine a target's location by comparing acquired magnetic field values with a magnetic field map containing pre-collected field values at different locations and choosing the location having the closest value. As the target moves, we use pedestrian dead reckoning to estimate the expected moving path, reducing the maximum positioning error of the initial location. The system eliminates the problem of localization error accumulation in pedestrian dead reckoning with the help of the fingerprinting and does not require Wi-Fi AP infrastructure, enabling cost-effective localization solution.

• Progress in Medical Physics
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• v.20 no.4
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• pp.324-330
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• 2009

In this study, we evaluated accuracy and usefulness of CyberKnife Respiratory Tracking System ($Synchrony^{TM}$, Accuray, USA) about a moving during stereotactic radiosurgery. For this study, we used moving phantom that can move the target. We also used Respiratory Tracking System called Synchrony of the Cyberknife in order to track the moving target. For treatment planning of the moving target, we obtained an image using 4D-CT. To measure dose distribution and point dose at the moving target, ion chamber (0.62 cc) and gafchromic EBT film were used. We compared dose distribution (80% isodose line of prescription dose) of static target to that of moving target in order to evaluate the accuracy of Respiratory Tracking System. We also measured the point dose at the target. The mean difference of synchronization for TLS (target localization system) and Synchrony were $11.5{\pm}3.09\;mm$ for desynchronization and $0.14{\pm}0.08\;mm$ for synchronization. The mean difference between static target plan and moving target plan using 4D CT images was $0.18{\pm}0.06\;mm$. And, the accuracy of Respiratory Tracking System was less 1 mm. Estimation of usefulness in Respiratory Tracking System was $17.39{\pm}0.14\;mm$ for inactivity and $1.37{\pm}0.11\;mm$ for activity. The mean difference of absolute dose was $0.68{\pm}0.38%$ in static target and $1.31{\pm}0.81%$ in moving target. As a conclusion, when we treat about the moving target, we consider that it is important to use 4D-CT and the Respiratory Tracking System. In this study, we confirmed the accuracy and usefulness of Respiratory Tracking System in the Cyberknife.

• International Journal of Control, Automation, and Systems
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• v.6 no.2
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• pp.204-213
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• 2008

In this paper, we present the practical application of an Unscented Kalman Filter (UKF) for an Indoor Mobile Localization System using ultrasonic sensors. It is true that many kinds of localization techniques have been researched for several years in order to contribute to the realization of a ubiquitous system; particularly, such a ubiquitous system needs a high degree of accuracy to be practical and efficient. Unfortunately, a number of localization systems for indoor space do not have sufficient accuracy to establish any special task such as precise position control of a moving target even though they require comparatively high developmental cost. Therefore, we developed an Indoor Mobile Localization System having high localization performance; specifically, the Unscented Kalman Filter is applied for improving the localization accuracy. In addition, we also present the additive filter named 'Pre-filtering' to compensate the performance of the estimation algorithm. Pre-filtering has been developed to overcome negative effects from unexpected external noise so that localization through the Unscented Kalman Filter has come to be stable. Moreover, we tried to demonstrate the performance comparison of the Unscented Kalman Filter and another estimation algorithm, such as the Unscented Particle Filter (UPF), through simulation for our system.