• Journal of Information Processing Systems
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• v.16 no.3
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• pp.639-647
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• 2020

In the vibration target localization algorithms based on time difference of arrival (TDOA), Fang algorithm is often used in practice because of its simple calculation. However, when the delay estimation error is large, the localization equation of Fang algorithm has no solution. In order to solve this problem, one dimensional search location algorithm based on TDOA is proposed in this paper. The concept of search is introduced in the algorithm. The distance d1 between any single sensor and the vibration target is considered as a search variable. The vibration target location is searched by changing the value of d1 in the two-dimensional plane. The experiment results show that the proposed algorithm is superior to traditional methods in localization accuracy.

• Journal of IKEEE
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• v.18 no.1
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• pp.57-63
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• 2014

This paper is to technically implement the sensing platform for Home-Wellness Robot. The self-Localization of indoor mobile robot is very important for the sophisticated trajectory control. In this paper, the robot's self-localization algorithm is designed by RF sensor network and fuzzy inference. The robot realizes its self-localization, using RFID sensors, through the collaboration algorithm which uses fuzzy inference for combining the strengths of triangulation and triangulation. For the triangulation self-Localization, RSSI is implemented. TOA method is used for realizing the triangulation self-localization. The final improved position is, through fuzzy inference, made by the fusion algorithm of the resultant coordinates from trilateration and triangulation in real time. In this paper, good performance of the proposed self-localization algorithm is confirmed through the results of a variety of experiments in the base of RFID sensor network and reader system.

• Computational Structural Engineering
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• v.10 no.3
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• pp.241-250
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• 1997

The strain localization of concrete is a phenomenon such that the deformation of concrete is localized in finite region along with softening behavior. The objective of this paper is to develop a plasticity and damage algorithm for the finite element analysis of the strain-localization in concrete. In this paper, concrete member under strain localization is modeled with localized zone and non-localized zone. For modeling of the localized zone in concrete under strain localization, a general Drucker-Prager failure criterion by which the nonlinear strain softening behavior of concrete after peak-stress can be considered is introduced in a thermodynamic formulation of the classical plasticity model. The return-mapping algorithm is used for the integration of the elasto-plastic rate equation and the consistent tangent modulus is also derived. For the modeling of non-localized zone in concrete under strain localization, a consistent nonlinear elastic-damage algorithm is developed by modifying the free energy in thermodynamics. Using finite element program implemented with the developed algorithm, strain localization behaviors for concrete specimens under compression are simulated.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.4B
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• pp.378-385
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• 2011

The three-dimensional triangulation algorithm that the beacon nodes can be allocated to dynamically in not the experimental region but the practical region is suggested, and the performance of the localization system adapting the suggested algorithm is analyzed. The suggested algorithm adapts the computation method of the three dimensional point that the surfaces of three spheres overlapped, while the traditional triangulation algorithm adapts the computation method of the two dimensional point that three circles are overlapped in order to compute the distance between beacon nodes and mobile node that means a radius. In addition to this, to analyze the performance of the localization system adapting the suggested algorithm, first of all, the allocation layout of beacon nodes is made, and the allocation layout is modeled by selection of ten random distance values between mobile node and beacon nodes for computer simulation of the practical model. Next, the two dimensional coordinator of mobile node that is calculated by the suggested algorithm and the traditional triangulation algorithm is compared with each other. The localization measuring performance about three dimensional coordinator(z axis) of the suggested algorithm is also obtained by comparing with that of the practical model.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38B no.1
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• pp.80-86
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• 2013

The 3-Dimensional(3D) localization system based on beacon expansion and coordinate-space disassembly for the design of the 3D localization system in indoor environment is proposed and the performance of the proposed system is analyzed in this paper. The localization ratio of the 3D localization system adapts the proposed algorithm is analyzed by the calculation of errors occurred in the coordinates that the mobile node locates. It is indicated that the average error distance of the 3D localization system adapts the proposed algorithm is less than that of the 3D localization system not adapts the proposed algorithm as 0.47m. The localization average distance error in 12 coordinates is indicated that the 1.5m case is less than 2.5m case as 0.38m by some experimentations under the condition that the distances between the ceiling and the mobile node are 1.5m and 2.5m measured from the ceiling respectively. It is seen that the 3D localization system based on beacon expansion and coordinate-space disassembly can improved the degradation of the quality of service that is caused by some conditions and performance differences in sensors.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.7
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• pp.9-17
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• 2014

This paper proposes a binary particle swarm optimization (BPSO) algorithm for distributed node localization in wireless sensor networks (WSNs). Each unknown node performs localization using the value of the measured distances from three or more neighboring anchors, i.e., nodes that know their location information. The node that is localized during the localization process is then used as another anchor for remaining nodes. The performances of particle swarm optimization (PSO) and BPSO in terms of localization error and computation time are compared by using simulations in Matlab. The simulation results indicate that PSO-based localization is more accurate. In contrast, BPSO algorithm performs faster for finding the location of unknown nodes for distributed localization. In addition, the effects of transmission range and number of anchor nodes on the localization error and computation time are investigated.

• 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 information and communication convergence engineering
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• v.10 no.4
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• pp.349-358
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• 2012

Over a wireless sensor network (WSN), accurate localization of sensor nodes is an important factor in enhancing the association between location information and sensory data. There are many research works on the development of a localization algorithm over three-dimensional (3D) space. Recently, the complexity-reduced 3D trilateration localization approach (COLA), simplifying the 3D computational overhead to 2D trilateration, was proposed. The method provides proper accuracy of location, but it has a high computational cost. Considering practical applications over resource constrained devices, it is necessary to strike a balance between accuracy and computational cost. In this paper, we present a novel 3D localization method based on the received signal strength indicator (RSSI) values of four anchor nodes, which are deployed in the initial setup process. This method provides accurate location estimation results with a reduced computational cost and a smaller number of anchor nodes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.7
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• pp.3480-3500
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• 2017

Accurate locating for the mobile target remains a challenge in various applications of wireless sensor networks (WSNs). Unfortunately, most of the typical localization algorithms perform well only in the WSN with densely distributed sensor nodes. The non-localizable problem is prone to happening when a target moves into the WSN with sparsely distributed sensor nodes. To solve this problem, we propose a collaborative and predictive localization algorithm (CPLA). The Gaussian mixture model (GMM) is introduced to predict the posterior trajectory for a mobile target by training its prior trajectory. In addition, the collaborative and predictive schemes are designed to solve the non-localizable problems in the two-anchor nodes locating, one-anchor node locating and non-anchor node locating situations. Simulation results prove that the CPLA exhibits higher localization accuracy than other tested predictive localization algorithms either in the WSN with sparsely distributed sensor nodes or in the WSN with densely distributed sensor nodes.

• International Journal of Control, Automation, and Systems
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• v.6 no.2
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• pp.204-213
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• 2008

In this paper, we present the practical application of an Unscented Kalman Filter (UKF) for an Indoor Mobile Localization System using ultrasonic sensors. It is true that many kinds of localization techniques have been researched for several years in order to contribute to the realization of a ubiquitous system; particularly, such a ubiquitous system needs a high degree of accuracy to be practical and efficient. Unfortunately, a number of localization systems for indoor space do not have sufficient accuracy to establish any special task such as precise position control of a moving target even though they require comparatively high developmental cost. Therefore, we developed an Indoor Mobile Localization System having high localization performance; specifically, the Unscented Kalman Filter is applied for improving the localization accuracy. In addition, we also present the additive filter named 'Pre-filtering' to compensate the performance of the estimation algorithm. Pre-filtering has been developed to overcome negative effects from unexpected external noise so that localization through the Unscented Kalman Filter has come to be stable. Moreover, we tried to demonstrate the performance comparison of the Unscented Kalman Filter and another estimation algorithm, such as the Unscented Particle Filter (UPF), through simulation for our system.