• 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.

• ETRI Journal
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• v.37 no.4
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• pp.707-716
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• 2015

The purpose of a localization system is to estimate the coordinates of the geographic location of a mobile device. The accuracy of wireless localization is influenced by nonline-of-sight (NLOS) errors in wireless sensor networks. In this paper, we present an improved time of arrival (TOA)-based localization method for wireless sensor networks. TOA-based localization estimates the geographic location of a mobile device using the distances between a mobile station (MS) and three or more base stations (BSs). However, each of the NLOS errors along a distance measured from an MS (device) to a BS (device) is different because of dissimilar obstacles in the direct signal path between the two devices. To accurately estimate the geographic location of a mobile device in TOA-based localization, we propose an optimized localization method with a BS selection scheme that selects three measured distances that contain a relatively small number of NLOS errors, in this paper. Performance evaluations are presented, and the experimental results are validated through comparisons of various localization methods with the proposed method.

• Journal of Positioning, Navigation, and Timing
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• v.5 no.1
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• pp.1-9
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• 2016

Range-based wireless localization system must measure accurate range between a mobile node (MN) and reference nodes. However, non-line-of-sight (NLOS) error caused by the spatial structures disturbs the localization system obtaining the accurate range measurements. Localization methods using the range measurements including NLOS error yield large localization error. But filter-based localization methods can provide comparatively accurate location solution. Motivated by the accuracy of the filter-based localization method, a filter residual-based NLOS error estimation method is presented in this paper. Range measurement-based residual contains NLOS error. By considering this factor with NLOS error properties, NLOS error is mitigated. Also a process noise covariance matrix tuning method is presented to reduce the time-delay estimation error caused by the single dynamic model-based filter when the speed or moving direction of a MN changes, that is the used dynamic model is not fit the current dynamic of a MN. The presented methods are evaluated by simulation allowing direct comparison between different localization methods. The simulation results show that the presented filter is more accurate than the iterative least squares- and extended Kalman filter-based localization methods.

• Journal of Korea Spatial Information System Society
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• v.11 no.2
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• pp.1-6
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• 2009

Localization of nodes is a key technology for application of wireless sensor network. Having a GPS receiver on every sensor node is costly. In the past, several approaches, including range-based and range-free, have been proposed to calculate positions for randomly deployed sensor nodes. Most of them use some special nodes, called anchor nodes, which are assumed to know their own locations. Other sensors compute their locations based on the information provided by these anchor nodes. This paper uses a single mobile anchor node to move in the sensing field and broadcast its current position periodically. We provide a weighted centroid localization algorithm that uses coefficients, which are decided by the influence of mobile anchor node to unknown nodes, to prompt localization accuracy. We also suggest a criterion which is used to select mobile anchor node which involve in computing the position of nodes for improving localization accuracy. Weighted centroid localization algorithm is simple, and no communication is needed while locating. The localization accuracy of weighted centroid localization algorithm is better than maximum likelihood estimation which is used very often. It can be applied to many applications.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2007.06a
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• pp.111-112
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• 2007

• Journal of Communications and Networks
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• v.7 no.4
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• pp.429-437
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• 2005

Sensor localization has become an essential requirement for realistic applications over wireless sensor networks (WSN). In this paper we propose an ad hoc localization algorithm that is infrastructure-free, anchor-free, and computationally efficient with reduced communication. A novel combination of distance and direction estimation technique is introduced to detect and estimate ranges between neighbors. Using this information we construct unidirectional coordinate systems to avoid the reflection ambiguity. We then compute node positions using a transformation matrix [T], which reduces the computational complexity of the localization algorithm while computing positions relative to the fixed coordinate system. Simulation results have shown that at a node degree of 9 we get $90\%$ localization with $20\%$ average localization error without using any error refining schemes.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.255-256
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• 2008

Distributed localization algorithms are required for large-scale wireless sensor network applications. In this paper, we introduce an efficient algorithm, termed weighted neighbor-node distribution localization(WNDL), which emphasizes simple refinement and low system-load for low-cost and low-rate wireless sensors. We inspect WNDL algorithm through MATLAB simulation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.3
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• pp.1083-1097
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• 2018

This paper presents a novel range-free localization algorithm based on quantum particle swarm optimization. The proposed algorithm is capable of estimating the distance between two non-neighboring sensors for multi-hop heterogeneous wireless sensor networks where all nodes' communication ranges are different. Firstly, we construct a new cumulative distribution function of expected hop progress for sensor nodes with different transmission capability. Then, the distance between any two nodes can be computed accurately and effectively by deriving the mathematical expectation of cumulative distribution function. Finally, quantum particle swarm optimization algorithm is used to improve the positioning accuracy. Simulation results show that the proposed algorithm is superior in the localization accuracy and efficiency when used in random and uniform placement of nodes for heterogeneous wireless sensor networks.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.8
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• pp.699-705
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• 2012

In this paper, an infrastructure-based localization method using underwater wireless sensor network (UWSN) is addressed. A localization using the UWSN is necessary to widen the usage of underwater applications, however it is very difficult to establish the UWSN due to the restrictions of water. In this paper, to extend the usage of UWSN at the infrastructure, we propose a sophisticated UWSN localization method using the Received Signal Strength Indicator (RSSI) of the electromagnetic waves. During the electromagnetic waves propagating in underwater, there arises a lot of attenuation according to the distance, while the attenuation shows uniformity according to the distance. Using this characteristics, the localization system in underwater infrastructure is proposed and the experimental results show the effectiveness.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.2
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• pp.253-270
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• 2013

To achieve accurate localization information, complex algorithms that have high computational complexity are usually implemented. In addition, many of these algorithms have been developed to overcome several limitations, e.g., obstruction interference in multi-path and non-line-of-sight (NLOS) environments. However, localization systems those have complex design experience latency when operating multiple mobile nodes occupying various channels and try to compensate for inaccurate distance values. To operate multiple mobile nodes concurrently, we propose a localization system with both low complexity and high accuracy and that is based on a chirp spread spectrum (CSS) radio. The proposed localization system is composed of accurate ranging values that are analyzed by simple linear regression that utilizes a Big-$O(n^2)$ of only a few data points and an algorithm with a self-calibration feature. The performance of the proposed localization system is verified by means of actual experiments. The results show a mean error of about 1 m and multiple mobile node operation in a $100{\times}35m^2$ environment under NLOS condition.