• Journal of information and communication convergence engineering
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• v.16 no.1
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• pp.6-11
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• 2018

It is important to find the random estimation points in wireless sensor network. A link quality indicator (LQI) is part of a network management service that is suitable for a ZigBee network and can be used for localization. The current quality of the received signal is referred as LQI. It is a technique to demodulate the received signal by accumulating the magnitude of the error between ideal constellations and the received signal. This proposed model accepts any number of random estimation point in the network and calculated its nearest anchor centroid node pair. Coordinates of the LQI sphere are calculated from the pair and are added iteratively to the initially estimated point. With the help of the LQI and weighted centroid localization, the proposed system finds the position of target node more accurately than the existing system by solving the problems related to higher error in terms of the distance and the deployment of nodes.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.5A
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• pp.521-528
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• 2011

In sensor network environment, it is very important to localize sensor nodes. In order to know the position of nodes without GPS signals, the anchor robot approach is representatively used. Therefore, in this paper, we propose 4-Robot Localization Scheme (4RLS) that uses four mobile robots to efficiently localize sensor nodes for the fast time. Then, we show the improved performance of 4RLS in comparison with previously used three robot scheme through the real implementation and analysis.

• Journal of KIISE:Information Networking
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• v.32 no.5
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• pp.574-582
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• 2005

Localization in wireless sensor networks is essential to important network functions such as event detection, geographic routing, and information tracking. Localization is to determine the locations of nodes when node connectivities are given. In this paper, centroid approach known as a distributed algorithm is extended to a centralized algorithm. The centralized algorithm has the advantage of simplicity. but does not have the disadvantage that each unknown node should be in transmission ranges of three fixed nodes at least. The algorithm shows that localization can be formulated to a linear system of equations. We mathematically show that the linear system have a unique solution. The unique solution indicates the locations of unknown nodes are capable of being uniquely determined.

• Journal of Korea Multimedia Society
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• v.9 no.2
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• pp.172-188
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• 2006

Sensor localization is one of the fundamental problems in wireless sensor networks. Previous localization algorithms can be classified into two categories, the GGB (Global Geometry-Based) approaches and the LGB (Local Geometry-Based). In the GGB approaches, there are a fixed set of reference nodes of which the coordinates are pre-determined. Other nodes determine their positions based on the distances from the fixed reference nodes. In the LGB approaches, meanwhile, the reference node set is not fixed, but grows up dynamically. Most GGB algorithms assume that the nodes are deployed in a convex shape area. They fail if either nodes are in a concave shape area or there are obstacles that block the communications between nodes. Meanwhile, the LGB approach is vulnerable to the errors in the distance estimations. In this paper, we propose new localization algorithms to cope with those two limits. The key technique employed in our algorithms is to determine, in a fully distributed fashion, if a node is in the line-of-sight from another. Based on the technique, we present two localization algorithms, one for anchor-based, another for anchor-free localization, and compare them with the previous algorithms.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.283-285
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• 2005

If the ubiquitous computing times come before long, Context Awareness will be prominent among improved computing functions which are serviced to user. It is the very sense network, new technology, that makes it possible to recognize circumstances.In a lot of research projects about sensor network, this paper proposes the efficient method of localization for sensor network. I propose the possibility of localization using wireless RSS with no modification of hardware for sensor node and then suggest the limitation factors of method for efficiently improving performance.

• 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.

• The KIPS Transactions:PartA
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• v.17A no.2
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• pp.53-62
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• 2010

Mobile Sensor Vehicles, nodes of Mobile Sensor Network, are navigating for a specific, maybe unknown, region. For the precise usage of MSN, MSV has to be able to do localization by integrating information through communication by each other. In addition, MSV should be localized with various sensors equipped. In this research, we propose a set of techniques that improve accuracy using human mimic by combining and exploiting the existing techniques such as Dead-Reckoning, Computer Vision and Received Signal Strength Identification.

• Journal of KIISE:Information Networking
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• v.37 no.5
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• pp.409-414
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• 2010

The applications based on geographical location are increasing rapidly in wireless sensor networks (WSN). Recently, various localization algorithms have been proposed but the majority of algorithms rely on the specific hardware to measure the distance from the signal sources. In this paper, we propose the Weighted Multiple Rings Localization(WMRL). We assume that each deployed anchor node may periodically emit the successive beacon signals of the different power level. Then, the beacon signals form the concentric rings depending on their emitted power level, theoretically. The proposed algorithm defines the different weighting factor based on the ratio of each radius of ring. Also, If a sensor node may listen, it can find the innermost ring of the propagated signal for each anchor node. Based on this information, the location of a sensor node is derived by a weighted sum of coordinates of the surrounding anchor nodes. Our proposed algorithm is fully distributed and does not require any additional hardwares and the unreliable distance indications such as RSSI and LQI. Nevertheless, the simulation results show that the WMRL with two rings twice outperforms centroid algorithm. In the case of WMRL with three rings, the accuracy is approximately equal to WCL(Weighted Centroid Localization).

• The Journal of Korea Robotics Society
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• v.11 no.3
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• pp.156-162
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• 2016

For the underwater localization, acoustic sensor systems are widely used due to greater penetration properties of acoustic signals in underwater environments. On the other hand, the good penetration property causes multipath and interference effects in structured environment too. To overcome this demerit, a localization method using the attenuation of electro-magnetic(EM) waves was proposed in several literatures, in which distance estimation and 2D-localization experiments show remarkable results. However, in 3D-localization application, the estimation difficulties increase due to the nonuniform (doughnut like) radiation pattern of an omni-directional antenna related to the depth direction. For solving this problem, we added a depth sensor for improving underwater 3D-localization with the EM wave method. A micro scale pressure sensor is located in the mobile node antenna, and the depth data from the pressure sensor is calibrated by the curve fitting algorithm. We adapted the depth(z) data to 3D EM wave pattern model for the error reduction of the localization. Finally, some experiments were executed for 3D localization with the fast calculation and less errors.

• 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.