• 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.

• International Journal of Control, Automation, and Systems
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• v.3 no.1
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• pp.1-14
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• 2005

This paper presents an obstacle detection algorithm based on the consecutive and the cooperative range sensor scanning schemes. For a known environment, a mobile robot scans the surroundings using a range sensor that can rotate 3600°. The environment is rebuilt using nodes of two adjacent walls. The robot configuration is then estimated and an obstacle is detected by comparing characteristic points of the sensor readings. In order to extract edges from noisy and inaccurate sensor readings, a filtering algorithm is developed. For multiple robot localization, a cooperative scanning method with sensor range limit is developed. Both are verified with simulation and experiments.

• 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.

• Proceedings of the Korea Information Processing Society Conference
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• 2010.11a
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• pp.837-840
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• 2010

Wireless Sensor Networks have been proposed for several location-dependent applications. For such systems, the cost and limitations of the hardware on sensing nodes prevent the use of range-based localization schemes that depend on absolute point to point distance estimates. Because coarse accuracy is sufficient for most sensor network applications, solutions in range-free localization are being pursued as a cost-effective alternative to more expensive range-based approaches. In this paper, we proposed a Coefficient Allocated DV-Hop (CA DV-Hop) algorithm which reduces node's location error by awarding a credit value with respect to number of hops of each anchor to an unknown node. Simulation results have verified the high estimation accuracy with our approach which outperforms the classical DV-Hop.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.2
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• pp.106-116
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• 2011

USN(Ubiquitous Sensor Network) environment permits us to access whatever information we want, whenever we want. The technologies to provide a basement to these environments premise an accurate location establishment. Especially, ITS(Intelligent Transportation Systems) is easily constructed by applying USN technology. Localization can be categorized as either Range-based or Range-free. Range-based is known to be not suitable for the localization based on sensor network, because of the irregularity of radio propagation and the additional device requirement. The other side, Range-free is much appropriated for the resource constrained sensor network because it can actively locate by means of the communication radio. But, generally the location accuracy of Range-free is low. Especially, it is very low in a low-density environment. So, these two methods have both merits and demerits. Therefore, it requires a new method to be able to improve tracking accuracy by combining the two methods. This paper proposes the tracking scheme based on range-hybrid, which can markedly enhance tracking accuracy by effectively using the information of surrounding nodes and the RSSI(Received Signal Strength Indication) that does not require additional hardware. Additionally, we present a method, which can improve the accuracy of vehicle tracking by adopting the prediction mechanism. Simulation results show that our method outperforms other methods in the transportation simulation environment.

• Journal of Korea Multimedia Society
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• v.15 no.10
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• pp.1228-1235
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• 2012

In this Paper, we propose an energy efficient localization technique based on WUSB (Wireless USB) over WBAN (Wireless Body Area Networks) protocol required for Wearable Computer systems. For this purpose, the proposed localization algorithm minimizes power consumption and estimates location without range information. It is executed independently on the basis of WUSB over WBAN protocol at each sensor node comprising peripherals of a wearable computer system. And it minimizes power consumption by estimating locations of sensor nodes with range-free method fast.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.11
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• pp.1092-1098
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• 2007

A mobile robot localization problem can be classified into following three sub-problems as an observation likelihood model, a motion model and a filtering technique. So far, we have developed the range sensor based, integrated localization scheme, which can be used in human-coexisting real environment such as a science museum and office buildings. From those experiences, we found out that there are several significant issues to be solved. In this paper, we focus on three key issues, and then illustrate our solutions to the presented problems. Three issues are listed as follows: (1) Investigation of design requirements of a desirable observation likelihood model, and performance analysis of our design (2) Performance evaluation of the localization result by computing the matching error (3) The semi-global localization scheme to deal with localization failure due to abrupt wheel slippage In this paper, we show the significance of each concept, developed solutions and the experimental results. Experiments were carried out in a typical modern building environment, and the results clearly show that the proposed solutions are useful to develop practical and integrated localization schemes.

• Journal of Digital Convergence
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• v.14 no.8
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• pp.261-267
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• 2016

In this paper, we studied the range-free localization algorithm between sensor nodes based on the Radical Line for sensor networks. Routing in wireless sensor networks should reduce the overall energy consumption of the sensor network, or induce equivalent energy consumption of all the sensor nodes. In particular, when the amount of data to send more data, the energy consumption becomes worse. New methods have been proposed to address this. So as to allow evenly control the overall energy consumption. For this, the paper covers designing a localization algorithm that can obtain the location information of the peripheral nodes with fewer operations. For the operation of the algorithm is applicable Radical Line. The experimental environment is windows 7, the Visual C ++ 2010, MSSQL 2008. The experimental results could be localized to perform an error rate of 0.1837.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.27-29
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• 2004

This paper presents a sensor model design based on Monte Carlo Localization method. First, we define the measurement error of each sample using a map matching method by 2-D laser scanners and a pre-constructed grid-map of the environment. Second, samples are assigned probabilities due to matching errors from the gaussian probability density function considered of the sample's convergence. Simulation using real environment data shows good localization results by the designed sensor model.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.2
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• pp.574-592
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• 2016

Range-free localization algorithm computes a normal node's position by estimating the distance to anchors which know their actual position. In recent years, reliable anchor selection research has been gained a lot of attention because this approach improves localization accuracy by selecting the only subset of anchors called reliable anchor. The distance estimation accuracy and the geometric shape formed by anchors are the two important factors which need to be considered when selecting the reliable anchors. In this paper, we study the relationship between a relative position of three anchors and localization error. From this study, under ideal condition, which is with zero localization error, we find two conditions for anchor selection, thereby proposing a novel anchor selection algorithm that selects three anchors matched most closely to the two conditions, and the validities of the conditions are proved using two theorems. By further employing the conditions, we finally propose a novel range-free localization algorithm. Simulation results show that the proposed algorithm shows considerably improved performance as compared to other existing works.