A three-dimension localization algorithm for wireless sensor network nodes based on SVM

Huan, Ruohong; Chen, Qingzhang; Mao, Keji; Pan, Yun

doi:10.1109/icgcs.2010.5542981

Cited by 17 publications

(9 citation statements)

References 6 publications

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“…Recently, researchers have proposed a number of 3D localization algorithm, such as Landscape-3D [4], T-3D [5], M-Based 3D Localization [6]. Common localization methods can be divided into two kind, they are distance based and distance independent.…”

Section: Sensor Localization Related Workmentioning

confidence: 99%

A Localization Algorithm of Multi-hop Three Dimensional AOA with Space-based Angle Transmission and Its Application

Chen¹,

Ni²,

Li³

et al. 2012

Proceedings of the 2012 2nd International Conference on Computer and Information Applications (ICCIA 2012)

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Abstract-Wireless sensor node's localization is a funda-mental technology in Wireless Sensor Networks. There are only quite a few study on three-dimensional (3D) localization which is suffered in slow progress, actually, is one of the main difficulties in WSN localization. Based on the study of the existing two-dimensional positioning algorithm and the application of terrain modeling, localization algorithm for sensor nodes in (3D) condition has been focus on as well as the application of terrain model. Using the idea proposed by representative algorithm--APS multi-hop AOA (Angle of Arrival), this paper proposed a new algorithm named Multi-hop Three Dimensional AOA With Space-based Angle Trans-mission (MSAT3D AOA). Using this technology, target nodes can use information of anchor nodes which are more than one hop away form. This paper also combined MSAT3D AOA algorithm with Delaunay triangulation algorithm for terrain modeling.

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Section: Sensor Localization Related Workmentioning

confidence: 99%

A Localization Algorithm of Multi-hop Three Dimensional AOA with Space-based Angle Transmission and Its Application

Chen¹,

Ni²,

Li³

et al. 2012

Proceedings of the 2012 2nd International Conference on Computer and Information Applications (ICCIA 2012)

Self Cite

View full text Add to dashboard Cite

show abstract

“…[15][16][17] In the past few years, the soft computing approaches have been used in some localization algorithms. [18][19][20][21][22][23][24][25][26][27][28][29][30][31][32][33][34][35][36] One of the most recognized soft computing algorithms is neural networks. The neural networks are machines that act like a human brain.…”

Section: Introductionmentioning

confidence: 99%

A new range‐free PCA‐based localization algorithm in wireless sensor networks

Banihashemian

Adibnia

2019

Int J Communication

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Summary Range‐free localization algorithms in wireless sensor networks have been an interesting field for researchers over the past few years. The combining of different requirements such as storage space, computational capacities, communication capabilities, and power efficiency is a challenging aspect of developing a localization algorithm. In this paper, a new range‐free localization algorithm, called PCAL, is proposed using soft computing techniques. The proposed method utilizes hop‐count distances as the data to train and build a neural network. Before feeding the data into the neural network for the purpose of training, the dimensionality of data is reduced by principal component analysis algorithm. The performance of the proposed algorithm is evaluated using simulation. The obtained results show that the proposed algorithm has a better performance in contrast to other algorithms based on storage space, communication overhead, and localization accuracy. Furthermore, the effect of various parameters on the PCAL algorithm is studied.

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“…[11][12][13][14][15][16] In learning-based approaches, a model is built based on training data gathered from the network, and then each sensor node can estimate position itself using trained model. 17 Therefore, learning approaches can be used in a distributed manner, and each sensor can be localized independently from other sensor nodes.…”

Section: Introductionmentioning

confidence: 99%

Localization algorithm for large-scale wireless sensor networks based on FCMTSR-support vector machine

Fang

Wei

2016

International Journal of Distributed Sensor Networks

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Sensor node localization is one of research hotspots in the applications of wireless sensor network field. A localization algorithm is proposed in this article which is based on improved support vector machine for large-scale wireless sensor networks. For a large-scale wireless sensor network, localization algorithm based on support vector machine faces to the problem of the large-scale learning samples. The large-scale training samples will lead to high burden of the training calculation, over learning, and low classification accuracy. In order to solve these problems, this article proposed a novel scale of training sample reduction method (FCMTSR). FCMTSR takes the training sample as point set, get the potential support vectors, and remove the non-boundary outlier data immixed by analyzing relationships between points and set. To reduce the calculation load, fuzzy C-means clustering algorithm is applied in the FCMTSR. By the FCMTSR, the training time is reduced and the localization accuracy is improved. Through the simulations, the performance of localization based on FCMTSR-support vector machine is evaluated. The results prove that the localization precision is improved 2%, the training time is reduce 55% than existing localization algorithm based on support vector machine without FCMTSR. FCMTSR-support vector machine localization algorithm also addresses the border problem and coverage hole problem effectively. Finally, the limitation of the proposed localization algorithm is discussed and future work is present.

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A three-dimension localization algorithm for wireless sensor network nodes based on SVM

Cited by 17 publications

References 6 publications

A Localization Algorithm of Multi-hop Three Dimensional AOA with Space-based Angle Transmission and Its Application

A Localization Algorithm of Multi-hop Three Dimensional AOA with Space-based Angle Transmission and Its Application

A new range‐free PCA‐based localization algorithm in wireless sensor networks

Localization algorithm for large-scale wireless sensor networks based on FCMTSR-support vector machine

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