• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.11
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• pp.2099-2106
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• 2006

In this paper, we addressed the node positioning method for minimizing the sensing energy consumption in wireless sensor networks with adjustable sensing ranges. It is necessary for minimizing the sensing energy consumption to minimize the overlapped sensing area by neighboring nodes. To find a optimal node position, we derived a optimal equations by using the overlapped areas, each node's radiuses and expended angles of opposite neighboring nodes. Based on it, we devised a new node positioning method, called as ASRC(Adjustable Sensing Ranges Control). Unlike existing condition based model, our proposed method was derived from mathematical formula, and we confirmed its validity of sensing energy consumption through simulations.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37B no.10
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• pp.889-900
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• 2012

In wireless sensor networks, the positioning scheme using received signal strength (RSS) has been widely considered. Appropriate estimation of path-loss exponent (PLE) between a sensor node and an anchor node plays a key role in reducing position error in this RSS-based positioning scheme. In the conventional researches, a sensor node directly uses the PLEs measured by its nearest anchor node to calculate its position. However, the actual PLE between a sensor node and the anchor node can be different from the PLE measured by its nearest anchor node. Thus, if a sensor node directly uses the PLEs measured by its nearest anchor node, the estimated position is different from the actual position of the sensor node with a high probability. In this paper, we describe the method how a sensor node estimates PLEs from the anchor nodes of interest by itself and calculates its position based on these self-estimated PLEs. Especially, our proposal suggests the mechanism to iteratively calculate the PLEs depending on the estimated distances between a sensor node and anchor nodes. Based on the recalculated PLEs, the sensor node reproduces its position. Through simulations, we show that our proposed positioning scheme outperforms the traditional scheme in terms of position error.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.10A
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• pp.784-795
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• 2009

An accurate positioning estimation in the wireless sensor networks (WSN) is very important in which each sensor node is aware of neighbor conditions. The multi-hop positioning estimation technique is considered as one of the suitable techniques for the WSN with many low power devices. However geographical holes, where there is no sensor node, may severely decrease the positioning accuracy so that the positioning error can be beyond the tolerable range. Therefore in this paper, we analyze error factors of DV-hop and hole effect to obtain node's accurate position. The proposed methods include boundary node detection, distance level adjustment, and unreliable anchor elimination. The simulation results show that the proposed method can achieve higher positioning accuracy using the hole detection and enhanced distance calculation methods compared with the conventional DV-hop.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.12A
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• pp.982-990
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• 2009

The IEEE 802.15.4 wireless sensor network is composed of the unique sensor devices to monitor and collect physical or environmental conditions. The interests in a positioning technology, which is one of the environment monitoring technologies, are gradually increased according to the development of the sensor technology and IT infrastructure. Generally, it is difficult for the positioning system using RSSI (Received Signal Strength Indication) based implementation to get accurate position because of obstacles, RF wave's delay and multipath. Therefore, in this paper, we investigate the improved positioning technologies for RSSI-based positioning system. This paper also proposes the enhanced scheme to improve the accuracy of positioning system by applying the Gaussian Filter algorithm, which is widely used for enhancing the performance of image processing system. For the implementation of proposed scheme, we firstly make a look-up tables, which represent the distance between target node and master node and corresponding RSSI value of each target node which are recorded as an average value after investigating the characteristics of attenuation of transmitted signal By applying the pre-determined look-up tables and Gaussian Filtering in the proposed scheme, we analyzed the positioning performance and compared with other conventional RSSI-based positioning algorithms.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.1
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• pp.198-205
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• 2007

In ubiquitous environment a user can be provided with context-aware services based on his or her current location, time, and atmosphere. LBS(Location-Based Services) play an important role for ubiquitous context-aware computing. Because deployment and maintenance of this specialized equipment is costly, many studies have been conducted on positioning using only wireless equipment under a wireless LAN infrastructure. Because a CPS(Cooperative Positioning System) that uses the RSSI (Received Signal Strength Indicator) between mobile equipments is more accurate than beacon based positioning system, it requires great concentration in its applications. This study investigates the relationship between nodes by analyzing a WiPS (Wireless LAN indoor Positioning System), a similar type of CPS, and proposes a improved WiCOPS-d(Wireless Cooperative Positioning System using node density) to increase performance by determining the convergence adjustment factor based on node density.

• Journal of IKEEE
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• v.26 no.1
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• pp.67-76
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• 2022

In this paper, we propose a new algorithm to improve the accuracy of the Wi-Fi access point (AP) positioning technique. The proposed algorithm based on evaluating the trustworthiness of the signal strength quality of each measurement node is superior to other existing AP positioning algorithms, such as the centroid, weighted centroid, multilateration, and radio distance ratio methods, owing to advantages such as reduction of distance errors during positioning, reduction of complexity, and ease of implementation. To validate the performance of the proposed algorithm, we conducted experiments in a complex indoor environment with multiple walls and obstacles, multiple office rooms, corridors, and lobby, and measured the corresponding AP signal strength value at several specific points based on their coordinates. Using the proposed algorithm, we can obtain more accurate positioning results of the APs for use in research or industrial applications, such as finding rogue APs, creating radio maps, or estimating the radio frequency propagation properties in an area.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.44 no.1
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• pp.10-18
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• 2007

In this paper, we address the node positioning method for minimizing the overlap sensing areas in wireless sensor networks with adjustable sensing ranges. To find a optimal node position, we derive a optimal equations by using the overlapped areas, each node's radiuses and expended angles of opposite neighboring nodes. Based on it, we devise a new node positioning method, called as ASRC(Adjustable Sensing Ranges Control). Unlike existing condition based model, our proposed method is derived from mathematical formula, and we confirm its validity through various simulations.

• 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.

• 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.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.187-189
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• 2009

Position estimation in indoor is significant problem, because GPS which is usually used for outdoor positioning cannot be utilized to indoor positioning. Sensor network can be a solution for the positioning. Recently, chirp spread spectrum(CSS) specified in IEEE 802.15.4a provides an ability of ranging. Based on the results of the ranging, a position of a CSS node can be calculated by using trilateration. In this case, Kalman filter can be applied to the trilateration because of the measurement noise. In this paper, we apply the unscented Kalman filter for the trilateration. The trilateration can be represented to a nonlinear state space equation, and the unscented Kalman filter is suitable for nonlinear state space equation. Through the experimental results. we show the accuracy of the estimated position.