• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.459-461
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• 2019

The location estimation algorithm in the existing wireless network uses a base station to estimate the absolute location of three or more in the state where the terminal is fixed. However, this paper suggests a location recognition algorithm that uses a mobile terminal to estimate the location of a mobile base station using a traverse technique using a three-way estimation.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.9
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• pp.1692-1698
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• 2010

In this paper we use wireless sensor network and ultrasonic sensors to estimate local position of mobile robots, and to navigate it. Ultra sonic sensor is simple and accurate so it is good to use in local estimation and navigation of mobile robots. But to obtain accurate distance of two sensors they need to face each others as possible as they can. To solve this problem we rotate ultra sonic sensor which is attached to robot in 360 degrees and obtain accurate distance. We can estimate precise position of mobile robot by triangulation using obtained distance information. A mobile robot navigates using embedded encoder and compensates its coordinates by ultrasonic sensors. Results of Experiments show proposed method obtains accurate distance between sensors and coordinates of position of robot. And mobile robots can navigate designated path well.

• Proceedings of the IEEK Conference
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• 2007.07a
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• pp.139-140
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• 2007

A purpose of this paper is to research a location estimation algorithm of node which considers outdoor environments. After analyzing existing range based location estimation algorithm and their performances, we proposed a suitable algorithm to outdoor environment.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.5
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• pp.265-271
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• 2023

Recently, location information services are gradually expanding due to the development of information and communication technology. RSSI is widely used to extract indoor and outdoor locations. The indoor and outdoor location estimation methods using RSSI are less accurate due to the influence of radio wave paths, interference, and surrounding wireless devices. In order to improve this problem, a distance estimation method that takes into account the wireless propagation environment is necessary. Therefore, in this study, we propose a distance estimation algorithm that takes into account the radio wave environment. The proposed method estimates the distance by learning RSSI input and output considering the RBF neural network and the propagation environment. To evaluate the performance of the proposed method, the performance of estimating the location of the receiver within a range of up to 55[m] using a BLE beacon transmitter and receiver was compared with the average filter and Kalman filter. As a result, the distance estimation accuracy of the proposed method was 6.7 times higher than that of the average filter and Kalman filter. As shown in the results of this performance evaluation, if the method of this study is applied to location services, more accurate location estimation will be possible.

• Journal of information and communication convergence engineering
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• v.10 no.3
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• pp.269-275
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• 2012

In this paper, we proposed a novel location estimation algorithm based on the concept of space-time signature matching in a moving target environment. In contrast to previous fingerprint-based approaches that rely on received signal strength (RSS) information only, the proposed algorithm uses angle, delay, and RSS information from the received signal to form a signature, which in turn is utilized for location estimation. We evaluated the performance of the proposed algorithm in terms of the average probability of error and the average error distance as a function of target movement. Simulation results confirmed the effectiveness of the proposed algorithm for location estimation even in moving target environment.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.9 no.6
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• pp.1653-1658
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• 2008

In this paper, it is analyzed propagation distribution characteristics of radio wave, which is radiated on all sides from Access Point device for estimating scheme of wireless AP without GPS receiver environment. To tracking AP device is traced from wireless terminals and wireless terminal is traced from fixed AP devices, above all it is important to analysis the characteristics of receiving power in according to distance. Therefore in this paper, radio propagation characteristics of 2.4GHz wave is analyzed effect extent and quality in according to distance in doors and out doors, and utilized to location estimation.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.9
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• pp.1935-1940
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• 2009

One of the key technical challenges of wireless sensor network (WSN) is location management of sensor nodes. Typical node location management methods use GPS, ultrasonic sensors or RSSI. In this paper we propose a new location management method which adopts regression analysis of RSSI measurement to improve the accuracy of sensor node position estimation. We also evaluated the performance of proposed method by comparing the experimental results with existing scheme. According to the results, our proposed method, LM-RAR, shows better accuracy than existing location management scheme using RSSI and Friis' equation.

• Journal of Advanced Marine Engineering and Technology
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• v.39 no.2
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• pp.187-194
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• 2015

Accurate relative location estimation is a key requirement in indoor localization systems based on wireless sensor networks (WSNs). However, although these systems have applied not only various optimization algorithms but also fusion with sensors to achieve high accuracy in position determination, they are difficult to provide accurate relative azimuth and locations to users because of cumulative errors in inertial sensors with time and the influence of external magnetic fields. This paper based on ultra-wideband positioning system, which is relatively suitable for indoor localization compared to other wireless communications, presents an indoor localization system for estimating relative azimuth and location of location-unaware nodes, referred to as target nodes without applying any algorithms with complex variable and constraints to achieve high accuracy. In the proposed method, the target nodes comprising three mobile nodes estimate the relative distance and azimuth from two reference nodes that can be installed by users. In addition, in the process of estimating the relative localization information acquired from the reference nodes, positioning errors are minimized through a novel modified rounding estimation technique in which Kalman filter is applied without any time consumption algorithms. Experimental results show the feasibility and validity of the proposed system.

• Journal of IKEEE
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• v.20 no.1
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• pp.1-8
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• 2016

In this paper, we propose an effective time-of-arrival (TOA)-based localization method with adaptive bias computation in indoor environments. The goal of the localization is to estimate an accurate target's location in wireless localization system. However, in indoor environments, non-line-of-sight (NLOS) errors block the signal propagation between target device and base station. The NLOS errors have significant effects on ranging between two devices for wireless localization. In TOA-based localization, finding the target's location inside the overlapped area in the TOA-circles is difficult. We present an effective localization method using compensated distance with adaptive bias computation. The proposed method is possible for the target's location to estimate an accurate location in the overlapped area using the measured distances with subtracted adaptive bias. Through localization experiments in indoor environments, estimation error is reduced comparing to the conventional localization methods.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.4
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• pp.378-384
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• 2015

Indoor localization is becoming one of the most important technologies for smart mobile applications with different requirements from conventional outdoor location estimation algorithms. Fingerprinting location estimation techniques based on neural networks have gained increasing attention from academia due to their good generalization properties. In this paper, we propose a novel location estimation algorithm based on an ensemble of multiple neural networks. The neural network ensemble has drawn much attention in various areas where one neural network fails to resolve and classify the given data due to its' inaccuracy, incompleteness, and ambiguity. To the best of our knowledge, this work is the first to enhance the location estimation accuracy in indoor wireless environments based on a neural network ensemble using fingerprinting training data. To evaluate the effectiveness of our proposed location estimation method, we conduct the numerical experiments using the TGn channel model that was developed by the 802.11n task group for evaluating high capacity WLAN technologies in indoor environments with multiple transmit and multiple receive antennas. The numerical results show that the proposed method based on the NNE technique outperforms the conventional methods and achieves very accurate estimation results even in environments with a low number of APs.