• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1162-1167
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• 2003

This paper presents a simple sensor network consists of a group of sensors, RF components, and microprocessors, to perform a distributed sensing and information transmission using wireless links. In the proposed sensor network, though each sensor node has a limited capability and a simple signal-processing engine, a group of sensor nodes can perform a various tasks through coordinated information sharing and wireless communication in a large working area. Using the capability of self-localization and tracking, we show the sensor network can be applied to localization and navigation of mobile robot in which the robot has to be coordinated effectively to perform given task in real time.

• Journal of the Korea Society of Computer and Information
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• v.12 no.4
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• pp.269-277
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• 2007

Wireless sensor network system is expected to get high attention in research for now and future owing to the advanced hardware development technology and its various applicabilities. Among variety of sensor network systems, the seashore and marine sensor network, which are extended to get sampling of marine resources, environmental monitoring to prevent disaster and to be applied to the area of sea route guidance. For these marine applications to be available, however, the provision of precise location information of every sensor nodes is essential. In this paper, the sequential localization algorithm for obtaining the location information of marine sensor nodes. The sequential localization is done with the utilization of a small number of beacon nodes along the seashore and gets the location of nodes by controling the sequences of localization and also minimizes the error accumulation. The key idea of this algorithm for localization is that the localization priority of each sensor nodes is determined by the number of reference nodes' information. This sequential algorithm shows the improved error performance and also provide the increased coverage of marine sensor network by enabling the maximum localization of sensor nodes as possible.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.3
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• pp.1014-1034
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• 2015

Location information of sensor nodes plays a critical role in many wireless sensor network (WSN) applications and protocols. Although many localization algorithms have been proposed in recent years, they usually target at dense networks and perform poorly in sparse networks. In this paper, we propose two component-based localization algorithms that can localize many more nodes in sparse networks than the state-of-the-art solution. We first develop the Basic Common nodes-based Localization Algorithm, namely BCLA, which uses both common nodes and measured distances between adjacent components to merge components. BCLA outperforms CALL, the state-of-the-art component-based localization algorithm that uses only distance measurements to merge components. In order to further improve the performance of BCLA, we further exploit the angular information among nodes to merge components, and propose the Component-based Localization with Angle and Distance information algorithm, namely CLAD. We prove the merging conditions for BCLA and CLAD, and evaluate their performance through extensive simulations. Simulations results show that, CLAD can locate more than 90 percent of nodes in a sparse network with average node degree 7.5, while CALL can locate only 78 percent of nodes in the same scenario.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.2
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• pp.385-390
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• 2008

The Study of environment monitoring through huge network of wireless sensor node is worked with activity. The sensor nodes must be very small, light and low cost. The localization which may determine where a given node is physically located in a network is one of the quite important problems for wireless sensor network. But simple localization method is required as excluding the usage of GPS(Global Positioning System) by the limit condition such as the node size, costs, and so on. In this paper, very simple method using connectivity for the outdoor RF communication environment is proposed. The proposed method is demonstrated through simulation.

• Journal of Engineering Education Research
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• v.13 no.2
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• pp.7-11
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• 2010

As the development of the computer and communication technologies, the ubiquitous society can be realized to the world early in the future. Thus, the localization system in Wireless Personal Area Network (WPAN) is required for many users of ubiquitous society to provide the ubiquitous computing based applications in respective of anytime and anywhere. In this paper, we propose the distance measurement scheme that is based on the distance measurement using RSSI (Received Signal Strength Indicator) of sensor module considering of two distance conditions for the localization system using Zigbee in WPAN. Also, the localization errors of the proposed scheme are analyzed in the three scenarios that the mobile module tracks in the in $6m{\times}6m$ scaled experimentation area. In addition to this, the monitoring subsystem is developed using GUI (Graphical User Interface) in order to monitor the location of the moving objects accurately and user-friendly.

• ETRI Journal
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• v.41 no.6
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• pp.782-796
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• 2019

This paper presents a hierarchical framework for managing the sampling distribution of a particle filter (PF) that estimates the global positions of mobile robots in a large-scale area. The key concept is to gradually improve the accuracy of the global localization by fusing sensor information with different characteristics. The sensor observations are the received signal strength indications (RSSIs) of Wi-Fi devices as network facilities and the range of a laser scanner. First, the RSSI data used for determining certain global areas within which the robot is located are represented as RSSI bins. In addition, the results of the RSSI bins contain the uncertainty of localization, which is utilized for calculating the optimal sampling size of the PF to cover the regions of the RSSI bins. The range data are then used to estimate the precise position of the robot in the regions of the RSSI bins using the core process of the PF. The experimental results demonstrate superior performance compared with other approaches in terms of the success rate of the global localization and the amount of computation for managing the optimal sampling size.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.6
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• pp.1291-1298
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• 2023

Surveillance reconnaissance sensor network is used for surveillance in wartime and area of operation. In this paper, we propose a target localization method using the detection signal strength of seismic sensors. Relay equipment calculates the target location using coordinate information and detection signal strength of the seismic sensors. Target localization error deviation due to environmental factors was minimized by subtracting the dynamic offset when calculating the target location. Field test shows improvement of target localization through reduction of errors. The average error was decreased to 3.62m. Up to 62% improved result was obtained compared to weighted centroid localization method.

• 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.

• Journal of the Korean Society of Industry Convergence
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• v.10 no.2
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• pp.105-113
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• 2007

Accurate and low-cost sensor localization is a critical requirement for the deployment of wireless sensor networks in a wide variety of application. Sensor position is used for its data to be meaningful and for energy efficient data routing algorithm especially geographic routing. The previous works for sensor localization utilize global positioning system(GPS) or estimate unknown-location nodes position with help of some small reference nodes which know their position previously. However, the traditional localization techniques are not well suited in the senor network for the cost of sensors is too high. In this paper, we propose the sensor localization method with a mobile robot, which knows its position, moves through the sensing field along pre-scheduled path and gives position information to the unknown-location nodes through wireless channel to estimate their position. We suggest using the sensor position estimation method and an efficient mobility path model. To validate our method, we carried out a computer simulation, and observed that our technique achieved sensor localization more accurately and efficiently than the conventional one.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.1
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• pp.61-80
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• 2018

Location information of individual nodes is important in the implementation of necessary network functions. While extensive studies focus on localization techniques in 2D space, few approaches have been proposed for 3D positioning, which brings the location closer to the reality with more complex calculation consumptions for high accuracy. In this paper, an effective range-free localization scheme is proposed for 3D space localization, and the sensitivity of parameters is evaluated. Firstly, we present an improved algorithm (MDV-Hop), that the average distance per hop of the anchor nodes is calculated by root-mean-square error (RMSE), and is dynamically corrected in groups with the weighted RMSE based on group hops. For more improvement in accuracy, we expand particle swarm optimization (PSO) of intelligent optimization algorithms to MDV-Hop localization algorithm, called PMDV-hop, in which the parameters (inertia weight and trust coefficient) in PSO are calculated dynamically. Secondly, the effect of various localization parameters affecting the PMDV-hop performance is also present. The simulation results show that PMDV-hop performs better in positioning accuracy with limited energy.