• Journal of Information Processing Systems
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• v.6 no.2
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• pp.147-162
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• 2010

In this paper, we present a fine-grained localization algorithm for wireless sensor networks using a mobile beacon node. The algorithm is based on distance measurement using RSSI. The beacon node is equipped with a GPS sender and RF (radio frequency) transmitter. Each stationary sensor node is equipped with a RF. The beacon node periodically broadcasts its location information, and stationary sensor nodes perceive their positions as beacon points. A sensor node's location is computed by measuring the distance to the beacon point using RSSI. Our proposed localization scheme is evaluated using OPNET 8.1 and compared with Ssu's and Yu's localization schemes. The results show that our localization scheme outperforms the other two schemes in terms of energy efficiency (overhead) and accuracy.

• Journal of Korea Spatial Information System Society
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• v.11 no.2
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• pp.1-6
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• 2009

Localization of nodes is a key technology for application of wireless sensor network. Having a GPS receiver on every sensor node is costly. In the past, several approaches, including range-based and range-free, have been proposed to calculate positions for randomly deployed sensor nodes. Most of them use some special nodes, called anchor nodes, which are assumed to know their own locations. Other sensors compute their locations based on the information provided by these anchor nodes. This paper uses a single mobile anchor node to move in the sensing field and broadcast its current position periodically. We provide a weighted centroid localization algorithm that uses coefficients, which are decided by the influence of mobile anchor node to unknown nodes, to prompt localization accuracy. We also suggest a criterion which is used to select mobile anchor node which involve in computing the position of nodes for improving localization accuracy. Weighted centroid localization algorithm is simple, and no communication is needed while locating. The localization accuracy of weighted centroid localization algorithm is better than maximum likelihood estimation which is used very often. It can be applied to many applications.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.2
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• pp.81-86
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• 2013

In this paper, the parameter identification for localization scheme for the optics-based micro sensor node is conducted. We analyzed short measurement range problem which can be occurred in optical based micro sensor node localization method using a time of flight. And we set up the theory for distance and maximum reflected laser power to overcome the problem by identifying hardware parameters like laser power, effective area of MEMS CCR, sensitivity of photodetector, and so on. Experimental results of measurement of maximum reflected laser power were compared with results of the theory. By using the theory, we can identify hardware parameters of localization scheme to measure particular position of the optics-based micro sensor node.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.3
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• pp.268-274
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• 2013

In this paper, the performance analysis of optics-based sensor node localization using ToF (Time of Flight) scheme is conducted. Generally, the position of the sensor node is calculated on the base station. And the base station scans neighboring sensor nodes with a laser. The laser which is reflected from one sensor node, however, can be reached to the base station at different angles according to the scanning resolution. This means that the error of the reached angle can increase and one node may be recognized as different nodes. Also the power of laser can decrease because the laser signal spread. Thus the sensor node which is located at a long distance from the base station cannot be detected. In order to overcome these problems which can be occurred in localization using ToF, the beam spot, the scanning resolution, the size of reflector and the power of laser at the sensor node were analyzed. It can be expected that the consequence of analysis can be provided in acquisition of accurate position of sensor node and construction of optics-based sensor node localization system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.8
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• pp.2627-2647
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• 2022

The easy scalability and low cost of range-free localization algorithms have led to their wide attention and application in node localization of wireless sensor networks. However, the existing range-free localization algorithms still have problems, such as large cumulative errors and poor localization performance. To solve these problems, an incremental strategy-based residual regression network is proposed for node localization in wireless sensor networks. The algorithm predicts the coordinates of the nodes to be solved by building a deep learning model and fine-tunes the prediction results by regression based on the intersection of the communication range between the predicted and real coordinates and the loss function, which improves the localization performance of the algorithm. Moreover, a correction scheme is proposed to correct the augmented data in the incremental strategy, which reduces the cumulative error generated during the algorithm localization. The analysis through simulation experiments demonstrates that our proposed algorithm has strong robustness and has obvious advantages in localization performance compared with other algorithms.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.10
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• pp.4971-4987
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• 2019

Node localization is the basic task of underwater wireless sensor networks (UWSNs). Most of the existing underwater localization methods rely on ranging accuracy. Due to the special environment conditions in the ocean, beacon nodes are difficult to deploy accurately. The narrow bandwidth and high delay of the underwater acoustic communication channel lead to large errors. In order to reduce the ranging error and improve the positioning accuracy, we propose a localization algorithm based on ranging correction and inertial coordination. The algorithm can be divided into two parts, Range Correction based Localization algorithm (RCL) and Inertial Coordination based Localization algorithm (ICL). RCL uses the geometric relationship between the node positions to correct the ranging error and obtain the exact node position. However, when the unknown node deviates from the deployment area with the movement of the water flow, it cannot communicate with enough beacon nodes in a certain period of time. In this case, the node uses ICL algorithm to combine position data with motion information of neighbor nodes to update its position. The simulation results show that the proposed algorithm greatly improves the positioning accuracy of unknown nodes compared with the existing localization methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.3
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• pp.901-920
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• 2015

Wireless Sensor Networks (WSNs) are widely used in geographically isolated applications like military border area monitoring, battle field surveillance, forest fire detection systems, etc. Uninterrupted power supply is not possible in isolated locations and hence sensor nodes live on their own battery power. Localization of sensor nodes in isolated locations is important to identify the location of event for further actions. Existing localization algorithms consume more energy at sensor nodes for computation and communication thereby reduce the lifetime of entire WSNs. Existing approaches also suffer with less localization coverage and localization accuracy. The objective of the proposed work is to increase the lifetime of WSNs while increasing the localization coverage and localization accuracy. A novel intelligent unmanned aerial vehicle anchor node (IUAN) is proposed to reduce the communication cost at sensor nodes during localization. Further, the localization computation cost is reduced at each sensor node by the proposed intelligent arc selection (IAS) algorithm. IUANs construct the location-distance messages (LDMs) for sensor nodes deployed in isolated locations and reach the Control Station (CS). Further, the CS aggregates the LDMs from different IUANs and computes the position of sensor nodes using IAS algorithm. The life time of WSN is analyzed in this paper to prove the efficiency of the proposed localization approach. The proposed localization approach considerably extends the lifetime of WSNs, localization coverage and localization accuracy in isolated environments.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.9
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• pp.925-930
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• 2008

Many sensor network applications require that each node's sensor data stream be annotated with its physical location in some coordinate system. Equipping GPS on every sensor node is often expensive and does not work in indoor deployments. Recently, cricket-based localization system is often used for indoor localization system. It is very important to know the exact position of beacons in cricket-based localization system for identifying moving sensor node's position. In this paper, a new method, Mobile Listener Detect Algorithm (MLD) which can automatically calculate the unknown newly installed beacons is proposed. For the verification of the feasibility of the proposed scheme, we have conducted several experiments.

• 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.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.2
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• pp.385-390
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• 2008

The Study of environment monitoring through huge network of wireless sensor node is worked with activity. The sensor nodes must be very small, light and low cost. The localization which may determine where a given node is physically located in a network is one of the quite important problems for wireless sensor network. But simple localization method is required as excluding the usage of GPS(Global Positioning System) by the limit condition such as the node size, costs, and so on. In this paper, very simple method using connectivity for the outdoor RF communication environment is proposed. The proposed method is demonstrated through simulation.