• Journal of information and communication convergence engineering
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• v.6 no.4
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• pp.459-465
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• 2008

Locations of nodes as well as gathered data from nodes are very important because generally multiple nodes are deployed randomly and data are gathered in wireless sensor network. Since the nodes composing wireless sensor network are low cost and low performance devices, it is very difficult to add specially designed devices for positioning into the nodes. Therefore in wireless sensor network, technology positioning nodes precisely using low cost is very important and valuable. This research proposes Cooperative Positioning System, which raises accuracy of location positioning and also can find positions on multiple sensors within limited times.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.1A
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• pp.65-75
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• 2009

In Wireless Sensor Network, the sensor node localization is important issue for information tracking, event detection, routing. Generally, in wireless sensor network localization, the absolute positions of certain anchor nodes are required based on the use of global positioning system, then all the other nodes are approximately localized using various algorithms based on a coordinate system of anchor DV-Hop is a localized, distributed, hop by hop positioning algorithm in wireless sensor network where only a limited fraction of nodes have self positioning capability. However, instead of uniformly distributed network, in anisotropic network with possible holes, DV-Hop's performance is very low. To address this issue, we propose Group based DV-Hop (GDV-Hop) algorithm. Best contribution of GDV-Hop is that it performs localization with reduced error compared with DV-Hop in anisotropic network.

• The Journal of the Korea institute of electronic communication sciences
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• v.5 no.4
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• pp.391-398
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• 2010

Because mobile sensor network is different with the existing wireless sensor network with fixed nodes, it is more difficult to implement a positioning algorithm in mobile sensor network than in mobile sensor network. In case of fast moving node, a positioning algorithm may be not completed in a given time. In this paper we present the positioning algorithm that improves performance and can complete a computation in time on mobile sensor network.

• Journal of Internet Computing and Services
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• v.10 no.1
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• pp.159-173
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• 2009

Locations of positioned nodes as well as gathered data from nodes are very important because generally multiple nodes are deployed randomly and data are gathered in wireless sensor network. Since the nodes composing wireless sensor network are low cost and low performance devices, it is very difficult to add specially designed devices for positioning into the nodes. Therefore in wireless sensor network, technology positioning nodes precisely using low cost is very important and valuable. This research proposes Cooperative Positioning System, which raises accuracy of location positioning and also can find positions on multiple sensors within limited times. And this research verifies this technology is excellent in terms of performance, accuracy, and scalability through simulation.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.11
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• pp.952-959
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• 2016

This paper proposes a novel indoor positioning system (IPS) that uses a calibrated camera sensor network and dense 3D map information. The proposed IPS information is obtained by generating a bird's-eye image from multiple camera images; thus, our proposed IPS can provide accurate position information when objects (e.g., the mobile robot or pedestrians) are detected from multiple camera views. We evaluate the proposed IPS in a real environment with moving objects in a wireless camera sensor network. The results demonstrate that the proposed IPS can provide accurate position information for moving objects. This can improve the localization performance for mobile robot operation.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.5
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• pp.889-896
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• 2022

Data required in a wireless sensor network environment requires more accurate figures as technology advances and its complexity increases. However, in the case of operating a large number of sensor nodes in a large area, the balance between the power consumed and the data quality that can be acquired accordingly should be considered for that purpose. In particular, in complex, densely populated urban areas or military operations with specific goals, location data requires increasingly detailed and high accuracy over a wide range. In this paper, we propose a method of mounting a Global Positioning System(: GPS) only on some of the sensor nodes deployed in the wireless sensor network and improving the error of GPS location data measured on that sensor node through Angle of Arrival(: AoA) and Received Signal Strength Indicator(: RSSI).

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.3
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• pp.243-257
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• 2010

Rapid developments in wireless sensor networks have extended many applications, hence, many studies have developed wireless sensor network positioning systems for indoor environments. Among those systems, the Global Position System (GPS) is unsuitable for indoor environments due to Line-Of-Sight (LOS) limitations, while the wireless sensor network is more suitable, given its advantages of low cost, easy installation, and low energy consumption. Due to the complex settings of indoor environments and the high demands for precision, the implementation of an indoor positioning system is difficult to construct. This study adopts a low-cost positioning method that does not require additional hardware, and uses the received signal strength (RSS) values from the receiver node to estimate the distance between the test objects. Since many objects in indoor environments would attenuate the radio signals and cause errors in estimation distances, knowing the path loss exponent (PLE) in an environment is crucial. However, most studies preset a fixed PLE, and then substitute it into a radio propagation loss model to estimate the distance between the test points; such method would lead to serious errors. To address this problem, this study proposes a Path Loss Exponent Estimation Algorithm, which uses only four beacon nodes to construct a radio propagation loss model for an indoor environment, and is able to provide enhanced positioning precision, accurate positioning services, low cost, and high efficiency.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.11
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• pp.4453-4468
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• 2015

This paper investigates optimization-based base station (BS) placement. An optimization model is defined and the BS placement problem is transformed to a lexicographical stratified programming (LSP) model for a given trajectory, according to different accuracy requirements. The feasible region for BS deployment is obtained from the positioning system requirement, which is also solved with signal coverage problem in BS placement. The LSP mathematical model is formulated with the average geometric dilution of precision (GDOP) as the criterion. To achieve an optimization solution, a tolerant factor based complete stratified series approach and grid searching method are utilized to obtain the possible optimal BS placement. Because of the LSP model utilization, the proposed algorithm has wider application scenarios with different accuracy requirements over different trajectory segments. Simulation results demonstrate that the proposed algorithm has better BS placement result than existing approaches for a given trajectory.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.9
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• pp.2120-2126
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• 2010

This paper aims to realize the location tracking system using the Zigbee in the wireless sensor network. The wireless sensor network offers the user-oriented location tracking service in the ubiquitous environment. The location tracking service can track the location of an object or a person and provides it. The location tracking system realized in this paper can be used inside or outside without any black-out areas to measure the location of the moving nodes. In tracking inside the RSSI signals use and in tracking outside will connect with the GPS signals to track the location. Also, by using Zigbee, the wireless sensor network environment was established and by obtaining the location of the moving nodes, the real-time tracking is possible.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.5
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• pp.1317-1340
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• 2024

With the rapid development of information technology, people's demands on precise indoor positioning are increasing. Wireless sensor network, as the most commonly used indoor positioning sensor, performs a vital part for precise indoor positioning. However, in indoor positioning, obstacles and other uncontrollable factors make the localization precision not very accurate. Ultra-wide band (UWB) can achieve high precision centimeter-level positioning capability. Inertial navigation system (INS), which is a totally independent system of guidance, has high positioning accuracy. The combination of UWB and INS can not only decrease the impact of non-line-of-sight (NLOS) on localization, but also solve the accumulated error problem of inertial navigation system. In the paper, a fused UWB and INS positioning method is presented. The UWB data is firstly clustered using the Fuzzy C-means (FCM). And the Z hypothesis testing is proposed to determine whether there is a NLOS distance on a link where a beacon node is located. If there is, then the beacon node is removed, and conversely used to localize the mobile node using Least Squares localization. When the number of remaining beacon nodes is less than three, a robust extended Kalman filter with M-estimation would be utilized for localizing mobile nodes. The UWB is merged with the INS data by using the extended Kalman filter to acquire the final location estimate. Simulation and experimental results indicate that the proposed method has superior localization precision in comparison with the current algorithms.