• Journal of the Korea Institute of Military Science and Technology
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• v.12 no.4
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• pp.437-445
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• 2009

In this paper, we present the performance of the LOB(line of bearing) - based emitter localization algorithm. The linear LSE(least-squared error) algorithm, nonlinear LSE algorithm and Stansfield algorithm are considered. In addition, we focus on the performance improvement of the weighted estimation compared with the unweighted estimation. Each estimation algorithm is briefly introduced, and the performance of the algorithm is illustrated using the numerical results.

• ETRI Journal
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• v.34 no.5
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• pp.684-689
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• 2012

A mode-singular-value-decomposition (SVD) maximum likelihood (ML) estimation procedure is proposed for the source localization problem under an additive measurement error model. In a practical situation, the noise variance is usually unknown. In this paper, we propose an algorithm that does not require the noise covariance matrix as a priori knowledge. In the proposed method, the weight is derived by the inverse of the noise magnitude square in the ML criterion. The performance of the proposed method outperforms that of the existing methods and approximates the Taylor-series ML and Cram$\acute{e}$r-Rao lower bound.

• Journal of information and communication convergence engineering
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• v.8 no.6
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• pp.709-715
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• 2010

This paper represents a map building and localization system for mobile robot. Map building and navigation is a complex problem because map integrity cannot be sustained by odometry alone due to errors introduced by wheel slippage, distortion and simple linealized odometry equation. For accurate localization, we propose sensor fusion system using encoder sensor and indoor GPS module as relative sensor and absolute sensor, respectively. To build a map, we developed a sensor based navigation algorithm and grid based map building algorithm based on Embedded Linux O.S. A wall following decision engine like an expert system was proposed for map building navigation. We proved this system's validity through field test.

• Proceedings of the KIEE Conference
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• 2002.11c
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• pp.501-504
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• 2002

This research embodied DGPS (Differential GPS) system that robot detects users present position in outside environment as part of Lacteal gland robot that is sight obstacle. Therefore, introduced GPS system that is effective means that can save essential world coordinate to realize global navigation. However, it is no the effectiveness to use GPS that is having error of tens meter to apply to lacteal gland robot that is sight obstacle without revision. Therefore, this research embodied Localization system of lacteal gland robot that is sight obstacle using DGPS that make use of FM DARC system to use DGPS to heighten navigation accuracy of this.

• Journal of Information Processing Systems
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• v.16 no.3
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• pp.639-647
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• 2020

In the vibration target localization algorithms based on time difference of arrival (TDOA), Fang algorithm is often used in practice because of its simple calculation. However, when the delay estimation error is large, the localization equation of Fang algorithm has no solution. In order to solve this problem, one dimensional search location algorithm based on TDOA is proposed in this paper. The concept of search is introduced in the algorithm. The distance d1 between any single sensor and the vibration target is considered as a search variable. The vibration target location is searched by changing the value of d1 in the two-dimensional plane. The experiment results show that the proposed algorithm is superior to traditional methods in localization accuracy.

• Annual Conference of KIPS
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• 2010.11a
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• pp.837-840
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• 2010

Wireless Sensor Networks have been proposed for several location-dependent applications. For such systems, the cost and limitations of the hardware on sensing nodes prevent the use of range-based localization schemes that depend on absolute point to point distance estimates. Because coarse accuracy is sufficient for most sensor network applications, solutions in range-free localization are being pursued as a cost-effective alternative to more expensive range-based approaches. In this paper, we proposed a Coefficient Allocated DV-Hop (CA DV-Hop) algorithm which reduces node's location error by awarding a credit value with respect to number of hops of each anchor to an unknown node. Simulation results have verified the high estimation accuracy with our approach which outperforms the classical DV-Hop.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.11
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• pp.3145-3162
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• 2023

As an important technology of the internetwork, wireless sensor network technique plays an important role in indoor localization. Non-line-of-sight (NLOS) problem has a large effect on indoor location accuracy. A location algorithm based on improved particle filter and directional probabilistic data association (IPF-DPDA) for WSN is proposed to solve NLOS issue in this paper. Firstly, the improved particle filter is proposed to reduce error of measuring distance. Then the hypothesis test is used to detect whether measurements are in LOS situations or NLOS situations for N different groups. When there are measurements in the validation gate, the corresponding association probabilities are applied to weight retained position estimate to gain final location estimation. We have improved the traditional data association and added directional information on the original basis. If the validation gate has no measured value, we make use of the Kalman prediction value to renew. Finally, simulation and experimental results show that compared with existing methods, the IPF-DPDA performance better.

• Journal of Advanced Navigation Technology
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• v.15 no.1
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• pp.83-90
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• 2011

The technique of localization is the core technology for information exchange or environment monitering to measure the position of an object or person. Today, the techniques of localization have been studied extensively and it can be applied to logistics, medical, robotics, etc. But, a lot of money to apply technique of localization is needed. Hence in this paper, we proposed AoA localization system based on Zigbee at low cost. The System measured the RSSI value by rotating the directional antenna using a step motor and Zigbee module. When the measured RSSI is the largest, the receiver measures the angles from beacons which are located at the corners with the rotating angle of a stepping motor and the position of the receiver will be calculated by appling AoA localization method. The measured results show an error about 35~36 cm.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.3
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• pp.499-505
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• 2016

In this Paper, we propose a body-area localization technique based on WUSB (Wireless USB) over WBAN (Wireless Body Area Networks) protocol required for wearable computer systems. The proposed localization algorithm is executed on the basis of WUSB over WBAN protocol at each sensor node comprising peripherals of a wearable computer system. To increase the accuracy of input information through various body motions in wearable computer systems, a new localization technique with high precision must be developed. To achieve the goal, This paper proposes a combined TDoA/FDoA/AoA (Time Of Arrival/Time Difference Of Arrival/Angle Of Arrival) localization technique with more than four WUSB over WBAN devices to estimate body-area location accurately. The combined TDoA/FDoA/AoA technique reduces 10mm in location estimation errors comparing with a combined TDoA/FDoA technique. This performance enhancement in location error reduction can be ignored at other systems but is meaningful results in body-area localization-based communications.

• The Journal of the Korea institute of electronic communication sciences
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• v.6 no.2
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• pp.288-295
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• 2011

The paper proposes a localization method of an underwater robot using Monte Carlo Localization(MCL) approach. Localization is one of the fundamental basics for autonomous navigation of an underwater robot. The proposed method resolves the problem of accumulation of position error which is fatal to dead reckoning method. It deals with uncertainty of the robot motion and uncertainty of sensor data in probabilistic approach. Especially, it can model the nonlinear motion transition and non Gaussian probabilistic sensor characteristics. In the paper, motion model is described using Euler angles to utilize the MCL algorithm for position estimation of an underwater robot. Motion model and sensor model are implemented and the performance of the proposed method is verified through simulation.