• Proceedings of the KIEE Conference
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• 2003.11b
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• pp.139-142
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• 2003

Location information of individual nodes is useful for routing and some other functions in wireless sensor networks. Each node can use GPS to know its position. However, the GPS service can not be practical to use due to cost efficiency, power, and computing capability. This paper proposes the localization method to make nodes know their location in case of a few nodes knows their position information. The proposed method is named as VALT (Virtual Anchor based Localization using Triangulation method). It uses the virtual anchor concept and calculates the location of individual nodes by means of the triangulation method. This method helps all nodes to determine their position with low cost and high scalability.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.48 no.6
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• pp.51-60
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• 2011

Researches on indoor localization using the wireless sensor network have been actively carried out to be used for indoor area where GPS signal is not received. Computationally efficient WCL(Weighted Centroid Localization) algorithm is shown to perform relatively well. However, to get the best performance for WCL all the anchor nodes must send signal with power to cover 96% of the network. The fact that outside the transmission range of the fixed nodes drastic localization error occurs results in large mean error and deviation. Due to these problems the WCL algorithm is not easily applied for use in the real indoor environment. In this paper we propose SRS(Succesive Region Setting) algorithm which sequentially reduces the estimated location area using the signal strength from the anchor nodes. The proposed algorithm does not show significant performance degradation corresponding to transmission range of the anchor nodes. Simulation results show that the proposed SRS algorithm has mean localization error 5 times lower than that of the WCL under free space propagation environment.

• Journal of the Korea Society of Computer and Information
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• v.15 no.1
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• pp.111-118
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• 2010

The proposed algorithm to be explained in this paper is the localization technique using directional antenna. Here, it is assumed that anchor node has the ability to transfer the azimuth of each sector using GPS modules, sector antenna, and the digital compass. In the conventional sensor network, the majority of localization algorithms were capable of estimating the position information of the sensor node by knowing at least 3 position values of anchor nodes. However, this paper has proposed localization algorithm that estimates the position of nodes to continuously move with sensor nodes and traveling nodes. The proposed localization mechanisms have been simulated in the Matlab. The simulation results show that our scheme performed better than other mechanisms (e.g. MCL, DV-distance).

• IEMEK Journal of Embedded Systems and Applications
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• v.5 no.4
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• pp.234-242
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• 2010

Two-way ranging methods such as TWR and SDS-TWR have been considered for many ranging systems because these methods are useful in the absence of synchronization. To estimate the location of a mobile node, complicated ranging procedures consisting of ranging frames between an anchor node and the mobile node are performed. Supporting multiple mobile nodes such as a few hundreds or thousands and several anchor nodes, the ranging procedures have the fatal disadvantage of processing delay and inefficient traffic bandwidth. On the other hand, the one-way ranging method is simple and fast, but susceptible to network synchronization. In this paper, we propose a method to modify asynchronous ranging equations to establish exact frequency or frequency offset, a method to estimate frequencies or frequency offsets, and a method to establish post-facto synchronization with anchor nodes. The synchronization for a node pair is adapted using instantaneous time information and corresponding difference of distances can be determined. We evaluate the performance of TWR, SDS-TWR and proposed ranging algorithms.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.5A
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• pp.521-528
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• 2011

In sensor network environment, it is very important to localize sensor nodes. In order to know the position of nodes without GPS signals, the anchor robot approach is representatively used. Therefore, in this paper, we propose 4-Robot Localization Scheme (4RLS) that uses four mobile robots to efficiently localize sensor nodes for the fast time. Then, we show the improved performance of 4RLS in comparison with previously used three robot scheme through the real implementation and analysis.

• ETRI Journal
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• v.31 no.4
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• pp.466-468
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• 2009

In this letter, we propose a one-way ranging algorithm that is based on wireless synchronization with measured timestamps and clock frequency offsets. In our proposed algorithm, an active mobile node initiates a ranging procedure by transmitting a ranging frame, and the anchor nodes report their timestamps for the received ranging frame to a reference anchor node. The synchronization of a pair of nodes is provided with instantaneous time information, and the corresponding difference of distances can be calculated.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.10
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• pp.4940-4957
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• 2019

Compared with the localization methods in the static sensor networks, node localization in dynamic sensor networks is more complicated due to the mobility of the nodes. Dynamic Sampling Localization Algorithm Based on Virtual Anchor (DSLA) is proposed in this paper to localize the unknown nodes in dynamic sensor networks. Firstly, DSLA algorithm predicts the speed and movement direction of nodes to determine a sector sampling area. Secondly, a method of calculating the sampling quantity with the size of the sampling area dynamically changing is proposed in this paper. Lastly, the virtual anchor node, i.e., the unknown node that got the preliminary possible area (PLA), assists the other unknown nodes to reduce their PLAs. The last PLA is regarded as a filtering condition to filter out the conflicting sample points quickly. In this way, the filtered sample is close to its real coordinates. The simulation results show that the DSLA algorithm can greatly improve the positioning performance when ensuring the execution time is shorter and the localization coverage rate is higher. The localization error of the DSLA algorithm can be dropped to about 20%.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.7B
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• pp.595-605
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• 2012

DV-Hop is one of the well known range-free localization algorithms. The algorithm works well in case of isotropic network since the sensor and anchor nodes are placed in the entire area. However, it results in large errors in case of anisotropic networks where the hop count between nodes is not linearly proportional to the Euclidean distance between them. Hence, we proposed a novel range-free algorithm for anisotropic networks to improve the localization accuracy. In the paper, the Euclidean distance between anchor node and unknown node is estimated by the average hop distance calculated at each hop count with hop count and distance information between anchor nodes. By estimating the unknown location of nodes with the estimated distance estimated by the average hop distance calculated at each hop, the localization accuracy is improved. Simulation results show that the proposed algorithm has more accuracy than DV-Hop.

• Journal of Korea Multimedia Society
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• v.9 no.2
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• pp.172-188
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• 2006

Sensor localization is one of the fundamental problems in wireless sensor networks. Previous localization algorithms can be classified into two categories, the GGB (Global Geometry-Based) approaches and the LGB (Local Geometry-Based). In the GGB approaches, there are a fixed set of reference nodes of which the coordinates are pre-determined. Other nodes determine their positions based on the distances from the fixed reference nodes. In the LGB approaches, meanwhile, the reference node set is not fixed, but grows up dynamically. Most GGB algorithms assume that the nodes are deployed in a convex shape area. They fail if either nodes are in a concave shape area or there are obstacles that block the communications between nodes. Meanwhile, the LGB approach is vulnerable to the errors in the distance estimations. In this paper, we propose new localization algorithms to cope with those two limits. The key technique employed in our algorithms is to determine, in a fully distributed fashion, if a node is in the line-of-sight from another. Based on the technique, we present two localization algorithms, one for anchor-based, another for anchor-free localization, and compare them with the previous algorithms.

• Journal of Information Processing Systems
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• v.16 no.5
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• pp.1158-1168
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• 2020

The distance vector-hop wireless sensor node location method is one of typical range-free location methods. In distance vector-hop location method, if a wireless node A can directly communicate with wireless sensor network nodes B and C at its communication range, the hop count from wireless sensor nodes A to B is considered to be the same as that form wireless sensor nodes A to C. However, the real distance between wireless sensor nodes A and B may be dissimilar to that between wireless sensor nodes A and C. Therefore, there may be a discrepancy between the real distance and the estimated hop count distance, and this will affect wireless sensor node location error of distance vector-hop method. To overcome this problem, it proposes a wireless sensor network node location method by modifying the method of distance estimation in the distance vector-hop method. Firstly, we set three different communication powers for each node. Different hop counts correspond to different communication powers; and so this makes the corresponding relationship between the real distance and hop count more accurate, and also reduces the distance error between the real and estimated distance in wireless sensor network. Secondly, distance difference between the estimated distance between wireless sensor network anchor nodes and their corresponding real distance is computed. The average value of distance errors that is computed in the second step is used to modify the estimated distance from the wireless sensor network anchor node to the unknown sensor node. The improved node location method has smaller node location error than the distance vector-hop algorithm and other improved location methods, which is proved by simulations.