• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2004.11a
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• pp.311-316
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• 2004

For the location estimation in the conventional LPMS(Loose Parts Monitoring System), it is popular to employ a group delay among the acoustic sensors installed within a 3 ft range from the impact source. However, there exists inherent error in determining the arrival time differences of the generated wave group among the neighboring sensors. To overcome this problem in this study, the two dimensional approach has been proposed and applied to effectively estimate the arrival time differences by using a continuous wavelet transform which is one of the linear time-frequency analysis methods. The experiment has been performed to both the plate model and the real steam generator in a nuclear power plant. It is expected that the reliability of the location estimation could be enhanced when the proposed time-frequency method is introduced into the LPMS system.

• Proceedings of the IEEK Conference
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• 2002.07c
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• pp.1610-1613
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• 2002

This paper analyses the performance of PE-IPDL technique fer the wireless mobile position location, which have been considered as a major candidate for 3GPP position location due to its capability in mitigating the hearability problem and DOP problem. To improve the location performance of PE-IPDL, this paper introduces the high-resolution estimation technique for the first arrival multipath delay, and simulation results verify its superiority. For a systematic analysis of above location method, its performances are exploited by obeying the CODIT channel model specially bad urban channel environment. Simulation results verify its efficiency of enhancing the degree of accuracy in positioning.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.4
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• pp.765-772
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• 2011

In this paper, a simulation-based method is presented to dispose direction finders in three dimensional space for locating targets using the directional data. A direction finder(DF) is a military weapon that is used to find locations of targets that emit radio frequencies by operating two or more DFs simultaneously. If one or more DFs are operated in the air, the accuracy of location estimation can be enhanced by disposing them in a better configuration. By extending the line method, which is a well-known algorithm for 2-D location estimation, into 3-D space, the problem of 3-D location estimation is defined as an nonlinear programming form and solved analytically. Then the optimal disposition of DFs is considered with the presented method in which methods of simulation and search technique are combined. With the suggested algorithm for 3-D disposition of DFs, regions in which targets exist can be effectively covered so that the operation effect of DF be increased.

• Journal of Korea Multimedia Society
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• v.19 no.2
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• pp.112-121
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• 2016

ADAS(Advanced Driver Assistance Systems) and street furniture information collecting car like as MMS(Mobile Mapping System), they require object location estimation method for recognizing spatial information of object in road images. But, the case of conventional methods, these methods require additional hardware module for gathering spatial information of object and have high computational complexity. In this paper, for a coordinate of road sign in single camera image, a position estimation scheme of object in road images is proposed using the relationship between the pixel and object size in real world. In this scheme, coordinate value and direction are used to get coordinate value of a road sign in images after estimating the equation related on pixel and real size of road sign. By experiments with test video set, it is confirmed that proposed method has high accuracy for mapping estimated object coordinate into commercial map. Therefore, proposed method can be used for MMS in commercial region.

• Journal of information and communication convergence engineering
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• v.8 no.2
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• pp.228-233
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• 2010

In this paper, the iteration localization algorithm that NLOS signal is iteratively removed to get the exact location in the wireless sensor network is proposed. To evaluate the performance of the proposed algorithm, TDOA location estimation method is used, and readers are located on every 150m intervals with rectangular shape in $300m{\times}300m$ searching field. In that searching field, the error distance is analyzed according to increasing the number of iteration, sub-blink and the estimated sensor node locations which are located in the iteration range. From simulation results, the error distance is diminished according to increasing the number of the sub-blink and iteration with the proposed location estimation algorithm in NLOS environment. Therefore, to get more accurate location information in wireless sensor network in NLOS environments, the proposed location estimation algorithm removing NLOS signal effects through iteration scheme is suitable.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.8
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• pp.752-759
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• 2008

In this paper, we propose a high accurate geo-location system based on a single base station, where its location is obtained by Time-of-Arrival(ToA) and Direction-of-Arrival(DoA) of the radio signal. For estimating accurate ToA and DoA information, a MUltiple SIgnal Classification(MUSIC) is adopted. However, the estimation of ToA and DoA using MUSIC algorithm is a time-consuming process. The position tracking bias is occurred by the time delay caused by the estimation process. In order to mitigate the bias error, we propose the estimation method of the position tracking bias and compensate the location error produced by the time delay using the position tracking bias mitigation. For accurate self-localization of mobile robot, the Unscented Kalman Filter(UKF) with position tracking bias is applied. The simulation results show the efficiency and accuracy of the proposed geo-location system and the enhanced performance when the Unscented Kalman Filter is adopted for mobile robot application.

• Journal of the Korean Statistical Society
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• v.31 no.2
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• pp.261-276
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• 2002

Probability density or its derivatives may have a discontinuity/change point at an unknown location. We propose a method of estimating the location and the jump size of the discontinuity point based on kernel type density or density derivatives estimators with one-sided equivalent kernels. The rates of convergence of the proposed estimators are derived, and the finite-sample performances of the methods are illustrated by simulated examples.

• Journal of the Korean Data and Information Science Society
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• v.17 no.1
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• pp.213-220
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• 2006

Since Beran (1977) developed the minimum Hellinger distance estimation, this method has been a popular topic in the field of robust estimation. In the process of defining a distance, a kernel density estimator has been widely used as a density estimator. In this article, however, we show that a combination of a kernel density estimator and an empirical density could result a smaller bias of the minimum Hellinger distance estimator than using just a kernel density estimator for a location parameter.

• Journal of Electrical Engineering and Technology
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• v.13 no.6
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• pp.2212-2219
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• 2018

This paper describes extended fault location algorithm using estimated remote source impedance. The method uses data only at the local end and the sequence current distribution factors for more accurate estimation. The proposed algorithm can respond to variation of the local and remote source impedance. Therefore, this method is especially useful for transmission lines interconnected to a wind farm that the source impedance varies continuously. The proposed algorithm is very insensitive to the variation in fault distance and fault resistance. The simulation results have shown the accuracy and effectiveness of the proposed algorithm.

• Communications for Statistical Applications and Methods
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• v.11 no.1
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• pp.153-160
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• 2004

In recent years, the size of data set which we usually handle is enormous, so a lot of outliers could be included in data set. Therefore the robust procedures that automatically handle outliers become very importance issue. We consider the robust estimation problem of location parameter in the univariate case. In this paper, we propose a new method for defining robustness weights for the weighted mean based on the median distance of observations and compare its performance with several existing robust estimators by a simulation study. It turns out that the proposed method is very competitive.