Positioning algorithm of heterogeneous wireless sensor network based on support vector regression

A support vector regression, wireless sensor technology, applied in satellite radio beacon positioning systems, location-based services, network planning and other directions, can solve problems such as high positioning accuracy

Inactive Publication Date: 2019-04-16
TIANJIN UNIVERSITY OF TECHNOLOGY
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Problems solved by technology

However, when the node density is as high as 0.03, the original EHP algorithm will have a higher positioning accuracy

Method used

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  • Positioning algorithm of heterogeneous wireless sensor network based on support vector regression
  • Positioning algorithm of heterogeneous wireless sensor network based on support vector regression
  • Positioning algorithm of heterogeneous wireless sensor network based on support vector regression

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Embodiment Construction

[0026] In order to further understand the content, characteristics and effects of the present invention, the following examples are given, and detailed descriptions are given below with reference to the accompanying drawings. It should be noted that this embodiment is descriptive, not restrictive, and cannot thereby limit the protection scope of the present invention.

[0027] A wireless sensor network positioning algorithm based on support vector regression machine, using the classic EHP method as the ranging formula (1), from the formula (1), it can be seen that the distance between two nodes includes E(d i-k ) and E(d k-j ), where E(d i-k ) represents the expected hop progress (Expected Hop progress, EHP), that is, the sum of the first hop distance and the middle hop distance; Represents the last-hop distance (Last-Hop Distance, LHD), and the precise distance matrix in the heterogeneous wireless sensor network is obtained by formula (1),

[0028]

[0029] Applying th...

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Abstract

The invention provides a positioning algorithm of a heterogeneous wireless sensor network based on a support vector regression. The output obtained by a training model is used as the coordinates of anunknown node, and the accuracy of the model is tested by using a standard root-mean-square error. The complexity is reduced by simplifying a CDF formula in a classical EHP algorithm, a calculated distance between a target anchor node and the unknown node is obtained at a higher convergence speed, and then training regression prediction is performed through the support vector regression (SVR) to obtain an accurate coordinate location of the unknown node. In order to reduce the number of anchor nodes, distance vectors between the target anchor nodes can be used as a training set of the model. By means of this manner, higher positioning accuracy and less overhead cost are ensured at the same time, and the potential useful information in the heterogeneous network is fully exploited by using the support vector regression to obtain a better positioning effect.

Description

technical field [0001] The invention belongs to the field of wireless sensor networks, in particular to a positioning algorithm for a heterogeneous wireless sensor network based on a support vector regression machine. Background technique [0002] In real life, heterogeneous wireless sensor networks are ubiquitous. There are many reasons for the heterogeneity of network nodes, such as different computing capabilities of nodes, differences in the quality of communication links, and differences in node energy. Therefore, in wireless sensor networks, it is difficult to ensure that network nodes have the same communication radius. However, for the convenience of research, most of the current algorithms are aimed at isomorphic WSNs. If these algorithms are applied to WSNs with large heterogeneity, this will undoubtedly greatly reduce the accuracy of positioning, because the difference in communication radius will greatly reduce the accuracy of the distance calculation formula b...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04W4/029H04W16/22H04W64/00G01S19/14H04W84/18
CPCG01S19/14H04W16/225H04W64/006H04W84/18H04W4/029
Inventor 温显斌文武武文兰
Owner TIANJIN UNIVERSITY OF TECHNOLOGY
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