• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.8C
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• pp.814-821
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• 2009

In an ultrawide band (UWB) indoor wireless localization, time of arrival (TOA) parameter estimation techniques have some difficulties in acquiring a reasonable TOA estimate because of the clustered multipath components overlapping or random time intervals mainly due to non line-of-sight (NLOS) environment. In order to solve that problem and achieve an excellent UWB indoor wireless localization, we propose a UWB signal model and a robust TOA parameter estimation technique that has little effect on the clustered problems unlike the conventional technique. Through simulation studies, the validity of the proposed model and the TOA estimation technique are examined. The performance of estimation error is also analyzed.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.3
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• pp.23-30
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• 2011

In the wireless sensor network(WSN), the detection of precise location of sensor nodes is essential for efficiently utilizing the sensing data acquired from sensor nodes. Among various location methods, the received signal strength (RSS) based localization scheme is mostly preferable in many applications since it can be easily implemented without any additional hardware cost. Since the RSS localization method is mainly effected by radio channel between two nodes, outlier data can be included in the received signal strength measurement specially when some obstacles move around the link between nodes. The outlier data can have bad effect on estimating the distance between two nodes such that it can cause location errors. In this paper, we propose a RSS-based localization method using Robust Statistic and Gaussian filter algorithm for enhancing the accuracy of RSS-based localization. In the proposed algorithm, the outlier data can be eliminated from samples by using the Robust Statistics as well as the Gaussian filter such that the accuracy of localization can be achieved. Through simulation, it is shown that the proposed algorithm can increase the accuracy of localization and is more robust to non gaussian noise channels.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.2
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• pp.114-119
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• 2009

Sound source localization systems in service robot applications estimate the direction of a human voice. Time delay information obtained from a few separate microphones is widely used for the estimation of the sound direction. Correlation is computed in order to calculate the time delay between two signals. Inverse cosine is used when the position of the maximum correlation value is converted to an angle. Because of nonlinear characteristic of inverse cosine, the accuracy of the computed angle is varied depending on the position of the specific sound source. In this paper, we propose an efficient sound source localization system using angle division. By the proposed approach, the region from $0^{\circ}$ to $180^{\circ}$ is divided into three regions and we consider only one of the three regions. Thus considerable amount of computation time is saved. Also, the accuracy of the computed angle is improved since the selected region corresponds to the linear part of the inverse cosine function. By simulations, it is shown that the error of the proposed algorithm is only 31% of that of the conventional a roach.

• The Journal of the Korea Contents Association
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• v.13 no.8
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• pp.11-19
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• 2013

This paper presents a simple method to estimate center of distortion and correct radial distortion from fish-eye lens. If the center of image is not locate that of lens in a straight line, the disadvantage of FOV model is low accurate because of correcting distortion without estimated centre of distortion. We propose a method accurately estimating Distortion center using FOV model and 2D pattern from wide angle lens. Our method determines the center of distortion in least error between straight lines and curves with FOV model. The results of experimental measurements on synthetic and real data are presented.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.7
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• pp.1524-1532
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• 2012

The calibration method using the existing environmental characteristics is to correct taking advantage of the data that is followed Judgement on the environment. If a decision is not made on the environmental judgement, the use of traditional methods may increase rather than errors. In this paper, UWB-based localization system is utilized. We propose Location Correction Algorithm which is available on if you can not make a judgment about any circumstances for location estimation system. Reference Points was selected to observe the characteristics of the localization system. This paper searched the characteristics of the localization system in LOS environment and NLOS environment, and used data correcting the location information of the moving object by combining the two environmental characteristics. The Location Correction Algorithm is applied to the location measured from the location estimation system. This algorithm corrects for the location information of the object. As a result, the location accuracy improvement were observed.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.245-246
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• 2008

변전소 모선에서 측정되는 전압, 전류를 기반으로 하는 CB기반 고장거리 추정기법은 배전선의 다중 분기선 때문에 다중개의 고장위치를 추론하는 것은 물론 분기 부하모델의 불확실성으로 인해 거리 계산에 오차를 포함하게 된다. 따라서 본 연구에서는 유비쿼터스 기반의 배전계통 하에서 구간 측정 전압, 전류 및 IED간 정보교환을 통해 얻어지는 전압, 전류 정보를 이용하여 고장경로를 추정하는 IED 기반 고장경로 추정기법을 제안한다.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.1
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• pp.15-21
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• 2011

In the range-based localization, the localization accuracy will be high dependent on the accuracy of distance measurement between two nodes. The received signal strength(RSS) is one of the simplest methods of distance measurement, and can be easily implemented in a ranging-based method. However, a RSS-based localization scheme has few problems. One problem is that the signal in the communication channel is affected by many factors such as fading, shadowing, obstacle, and etc, which makes the error of distance measurement occur and the localization accuracy of sensor node be low. The other problem is that the sensor node estimates its location for itself in most cases of the RSS-based localization schemes, which makes the sensor network life time be reduced due to the battery limit of sensor nodes. Since beacon nodes usually have more resources than sensor nodes in terms of computation ability and battery, the beacon node based localization scheme can expand the life time of the sensor network. In this paper, therefore we propose a beacon node based localization algorithm using received signal strength(RSS) and path loss calibration in order to overcome the aforementioned problems. Through simulations, we prove the efficiency of the proposed scheme.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.1880-1881
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• 2011

본 논문에서는 2차원 평면상을 주행하는 이동 로봇의 목표물에 대한 상대 위치 및 방향각을 측정하는 방법에 대하여 제안한다. 측정을 위해 사용되는 센서는 스테레오 카메라로, 이동 로봇은 3DOF의 특징을 갖고 있으므로 두 개의 점을 이용하여 상대 위치 및 방향각을 측정하는 방법을 제안한다. 상대 위치를 측정하는 과정에서 외란에 의한 위치 오차가 발생하게 되며, 이에 대한 대책으로 칼만 필터를 적용하여 더욱 강건한 상대 위치 추정을 한다. 마지막으로 MATLAB을 이용한 시뮬레이션을 통하여 외란이 존재하는 환경 하에서 제안된 시스템의 성능을 확인한다.

• Journal of the Korea Society of Computer and Information
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• v.12 no.5
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• pp.155-162
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• 2007

For providing smart home service, middleware technologies for electronic appliance control by network and user location information for location based service are important. Recently research using ultrasonic and radio signal are affected by the obstacle. In this paper, we suggest inertial sensor that is not affected by the obstacle. Also, we use RFID for initializing position. It solve error accumulation and position initialize problem. In this paper, we suggest following system for smarthome service and localization. This system are composed smarthome middleware, user localization system on middleware, inertial sensor and RFID Reader. This system shows operation without affect of obstacle in smarthome environment.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.12
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• pp.1207-1215
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• 2013

This paper proposes the location estimation techniques of distributed targets with the multi-sensor data perceived through IR sensors of the military robots in consideration of obstacles. In order to match up targets with measured azimuths, to add to the depth-first search (DFS) algorithms in free-obstacle environment, we suggest the expanded DFS (EDS) algorithm including bypass path search, partial path search, middle level ending, and the supplementation of decision metric. After matching up targets with azimuths, we estimate the coordinate of each target by obtaining the intersection point of the azimuths with the least square error (LSE) algorithm. The experimental results show the error rate of estimated location, mean number of calculating nodes, and mean distance between real coordinates and estimated coordinates of the proposed algorithms.