• Proceedings of the IEEK Conference
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• 2003.07c
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• pp.2581-2584
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• 2003

In this paper, we propose a self-localization algorithm using vertical line segments. Indoor environment is consist of horizontal and vertical line features such as doors, furniture, and so on. From the input image, vertical line edges are detected by an edge operator, Then, line segments are obtained by projecting edge image vertically and detecting local maximum from the projected histogram. From the relation of horizontal position of line segments and the location of the robot, nonlinear equations are come out Localization is done by solving the equations by using Newton's method. Experimental results show that the proposed algorithm using one camera is simple and applicable to indoor environment.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.6
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• pp.610-618
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• 2011

For improved localization around the indoor/outdoor transit area of buildings, this paper proposes an efficient algorithm combining the measurements from the WLAN (Wireless Local Area Network) and the GPS (Global Positioning System) for. The proposed hybrid localization algorithm considers both multipath errors and NLOS (Non-Line-of-Sight) errors, which occur in most wireless localization systems. To detect and isolate multipath errors occurring in GPS measurements, the propose algorithm utilizes conventional multipath test statistics. To convert WLAN signal strength measurements to range estimates in the presence of NLOS errors, a simple and effective calibration algorithm is designed to compute conversion parameters. By selecting and combining the reliable GPS and WLAN measurements, the proposed hybrid localization algorithm provides more accurate location estimates. An experiment result demonstrates the performance of the proposed algorithm.

• 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.

• Journal of Internet Computing and Services
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• v.11 no.1
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• pp.27-33
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• 2010

This paper applies Bayesian Markov inferred localization techniques for determining ZigBee mobile device's position. To evaluate its accuracy, we compare it with conventional technique, map-based localization. While the map-based localization technique referring to database of predefined locations and their RSSI data, the Bayesian Markov inferred localization is influenced by changes of time, direction and distance. All determinations are drawn from the estimation of Received Signal Strength (RSS) using ZigBee modules. Our results show the relationship between RSSI and distance in indoor ZigBee environment and higher localization accuracy of Bayesian Markov localization technique. We conclude that map-based localization is not suitable for flexible changes in indoors because of its predefined condition setup and lower accuracy comparing to distance-based Markov Chain inference localization system.

• Spatial Information Research
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• v.16 no.4
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• pp.455-465
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• 2008

Augmented reality (AR) has tremendous potential in visualizing geospatial information, especially on the actual physical scenes. However, to utilize augmented reality in mobile system, many researches have undergone with GPS or ubiquitous marker based approaches. Although there are several papers written with vision based markerless tracking, previous approaches provide fairly good results only in largely under "controlled environments." Localization and tracking of current position become more complex problem when it is used in indoor environments. Many proposed Radio Frequency (RF) based tracking and localization. However, it does cause deployment problems of large RF-based sensors and readers. In this paper, we present a noble markerless AR approach for indoor (possible outdoor, too) navigation system only using monoSLAM (Monocular Simultaneous Localization and Map building) algorithm to full-fill our grand effort to develop mobile seamless indoor/outdoor u-GIS system. The paper briefly explains the basic SLAM algorithm, then the implementation of our system.

• 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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.2
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• pp.703-722
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• 2016

Passive wireless devices have increasing civilian and military applications, especially in the scenario with wearable devices and Internet of Things. In this paper, we study indoor localization of a target equipped with radio-frequency identification (RFID) device in ultra-wideband (UWB) wireless networks. With known room layout, deterministic multipath components, including the line-of-sight (LOS) signal and the reflected signals via multipath propagation, are employed to locate the target with one transmitter and a single inaccurate receiver. A factor graph corresponding to the joint posterior position distribution of target and receiver is constructed. However, due to the mixed distribution in the factor node of likelihood function, the expressions of messages are intractable by directly applying belief propagation on factor graph. To this end, we approximate the messages by Gaussian distribution via minimizing the Kullback-Leibler divergence (KLD) between them. Accordingly, a parametric message passing algorithm for indoor passive localization is derived, in which only the means and variances of Gaussian distributions have to be updated. Performance of the proposed algorithm and the impact of critical parameters are evaluated by Monte Carlo simulations, which demonstrate the superior performance in localization accuracy and the robustness to the statistics of multipath channels.

• Journal of Advanced Marine Engineering and Technology
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• v.37 no.8
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• pp.932-938
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• 2013

Recently, the Fingerprint, which is one of the methods of indoor localization using WLAN, has been many studied owing to robustness about ranging error by the diffraction and refraction of radio waves. However, in the signal gathering process and comparison operation for the measured signals with the database, this method requires time consumption and computational complexity. In order to compensate for these problems, this paper presents, based on proposed modified database, WLAN indoor localization algorithm using selective operation of collected signal in real time. The proposed algorithm reduces the configuration time and the size of the data in the database through linear interpolation and thresholding according to the signal strength, the localization accuracy, while reducing the computational complexity, is maintained through selective operation of the signals which are measured in real time. The experimental results show that the accuracy of localization is improved to 17.8% and the computational complexity reduced to 46% compared to conventional Fingerprint in the corridor by using proposed algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.8
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• pp.1643-1654
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• 2015

With standardization of IEEE 802.11n, APs with the 2.4GHz and 5GHz dual-band capability have widely been deployed over a metropolitan area by individuals and internet service providers. Moreover, due to the increasing attentions on indoor-localization technique using Wi-Fi, the need for LOS and NLOS determination scheme is increasing to enhance accuracy of the localization. In this paper, we propose a novel LOS/NLOS determination technique by using different radio attenuation characteristics in different frequency bands and different mediums. Based on this technique, we designed a LOS/NLOS-aware indoor localization scheme. The proposed LOS/NLOS determination algorithm can be used when the distance between an user device and an AP is unknown, and the proposed localization scheme provides very accurate room-level position information. We validated the proposed scheme by implementing it on Android smart phones.

• Journal of KIISE:Information Networking
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• v.37 no.6
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• pp.489-493
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• 2010

In an indoor localization method taking the lateration-based approach, the distance between a target and an AP (Anchor Point) is estimated using RSS (Received Signal Strength) measurements. Since the characteristics of a radio signal randomly vary in time and space, errors are unavoidable in distance estimation with measured RSS. Since the accuracy of distance estimation affects the localization accuracy of a lateration-based method, additional APs hearing a target have been used for localization in the literature. However, lots of experimental results show that the accuracy of a lateration-based method is improved by using carefully selected APs measuring the high quality RSSs which the distances estimated is close to the actual distances between nodes as reference APs, not using merely more APs. In this paper, we focus on selection method of reference AP and distance estimation method reflecting on environmental dynamics. We validate our method by implementing an indoor localization system and evaluating the accuracy of our method in the various experimental environments.