Range-Free Distance Estimate Methods Using Neighbor Information in Wireless Sensor Networks

Cao, Yu; Chen, Xiupeng; Yu, Yang; Kang, Guixia

doi:10.1109/vetecf.2009.5379081

Cited by 7 publications

(2 citation statements)

References 10 publications

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“…Considering this situation, we propose a threshold of hop counts. In [20], the limitation of hop count is used to improve the localization accuracy and avoid the bad influence caused by path roundabout. According to the experience, the hop count threshold is set as 5 in this paper.…”

Section: Formation Of Voronoi Diagram In Localization Networkmentioning

confidence: 99%

Improved Normalized Collinearity DV-Hop Algorithm for Node Localization in Wireless Sensor Network

Zhang

Shu

et al. 2014

International Journal of Distributed Sensor Networks

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In recent years, collinearity theory is widely used in large-scale sensor network. When the anchor nodes are located at almost a straight line, the collinearity phenomenon will happen and usually cause negative influence on positioning accuracy. From detailed analysis of the relation between DV-Hop localization error and the collinearity, we proposed to select the anchor nodes which can meet the condition of hop count threshold and collinearity to participate in the localization procedure. Since there is uncertain situation that the anchor node's region is hard to be decided for the sensor nodes in one hop area, Voronoi diagram is adopted to divide the sensor network into several regions. Then, we can get the anchor node information in each Voronoi polygon. With this information and the collinearity condition, we can estimate the unknown node's position with relatively higher accuracy. Compared with the traditional DV-Hop and collinearity algorithm, our proposed algorithm can get better positioning accuracy in both homogeneous network and anisotropic network.

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Section: Formation Of Voronoi Diagram In Localization Networkmentioning

confidence: 99%

Improved Normalized Collinearity DV-Hop Algorithm for Node Localization in Wireless Sensor Network

Zhang

Shu

et al. 2014

International Journal of Distributed Sensor Networks

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“…In addition, the information of neighbours can be utilised to improve the positioning accuracy [22]. The hop count‐based neighbour partition [23, 24] utilised the number of neighbours with hop count h ± 1 to improve the distance estimation.…”

Section: Related Workmentioning

confidence: 99%

Improved localisation method based on multi‐hop distance unbiased estimation

2014

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Range-free, distributed localisation method is a challenging issue in wireless sensor networks (WSN). Typical hop count-based localisation methods assume that the Hopsize for different hop count is the same. However, many observations in WSN indicate that this assumption does not always correspond to the practical situation. In this study, the authors propose an approximate distribution of k-hop node distance and derive the expectation of k-hop node distance under the above distribution. Furthermore, the authors propose a novel range-free localisation method based on the multi-hop distance unbiased estimation (MDUE), and the simulation results demonstrate that more accurate distance and localisation can be obtained by MDUE than the state-of-the-art methods.

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On Improving Connectivity‐based Localization in Wireless Sensor Networks

Wang¹

2017

Wireless Sensor Systems for Extreme Environments

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Range-Free Distance Estimate Methods Using Neighbor Information in Wireless Sensor Networks

Cited by 7 publications

References 10 publications

Improved Normalized Collinearity DV-Hop Algorithm for Node Localization in Wireless Sensor Network

Improved Normalized Collinearity DV-Hop Algorithm for Node Localization in Wireless Sensor Network

Improved localisation method based on multi‐hop distance unbiased estimation

On Improving Connectivity‐based Localization in Wireless Sensor Networks

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