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Small-error positioning method for wireless sensor network

A wireless sensor and positioning method technology, applied in positioning, wireless communication, radio wave measurement system, etc., can solve the problems of less distribution of nodes, discrete, iterative errors, etc.

Active Publication Date: 2015-04-22
INFORMATION & TELECOMM COMPANY SICHUAN ELECTRIC POWER +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, in the actual network, there are fewer nodes and the distribution is discrete, which is easy to cause iteration errors

Method used

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  • Small-error positioning method for wireless sensor network
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  • Small-error positioning method for wireless sensor network

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0055] Such as Figure 1 to Figure 6 shown.

[0056] The parameter design of the network is shown in Table 1.

[0057] Table 1 Simulation parameter settings

[0058]

[0059] Such as figure 2 As shown in the initial node distribution diagram, where * mark points are the distribution of known nodes (beacon nodes), ● is the distribution of unknown nodes, in this figure, there are 20 beacon nodes, 80 unknown nodes, and there are 100 nodes.

[0060] Therefore, the coordinates of beacon nodes 1, 2, 3, 4, ..., 20 in the wireless sensor network are (x 1 ,y 1 ),(x 2 ,y 2 ),(x 3 ,y 3 ),...,(x 20 ,y 20 ), the coordinates of the unknown node C are (x, y); including the following steps:

[0061] Step A: Through a typical distance vector exchange protocol, each beacon node in the network broadcasts its own location information packet to neighboring nodes, so that all nodes in the network obtain the minimum hop information from the beacon node, so that all nodes record The ...

Embodiment 2

[0076] Such as Figure 1 to Figure 6 shown.

[0077] The parameter design of the network is shown in Table 1.

[0078] Table 1 parameter setting

[0079]

[0080]

[0081] Such as figure 2 As shown in the initial node distribution diagram, where * mark points are the distribution of known nodes (beacon nodes), ● is the distribution of unknown nodes, in this figure, there are 20 beacon nodes, 80 unknown nodes, and there are 100 nodes.

[0082] Therefore, the coordinates of beacon nodes 1, 2, 3, 4, ..., 20 in the wireless sensor network are (x 1 ,y 1 ),(x 2 ,y 2 ),(x 3 ,y 3 ),...,(x 20 ,y 20 ), the coordinates of the unknown node C are (x, y); including the following steps:

[0083] Step A: Through a typical distance vector exchange protocol, each beacon node in the network propagates its own location information packet to neighboring nodes, so that all nodes in the network obtain the minimum hop information from the beacon node, so that all nodes record The ...

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Abstract

The invention discloses a small-error positioning method for a wireless sensor network, and provides two improved DV-Hop positioning algorithms, a mandist weighted least square method and a dist weighted least square method. According to the two algorithms, minimum hop mandist weighted processing and minimum hop dist weighted processing are carried out on the average hop distance with a large error in a classical DV-Hop algorithm, and therefore the average hop distance can be estimated more effectively through the improved DV-Hop algorithms. As is shown in a simulation result, compared with the classical DV-Hop algorithm, the average positioning error of the two improved algorithms is reduced, and the positioning accuracy of the two improved algorithms is more stable.

Description

technical field [0001] The invention relates to the field of positioning of wireless sensor nodes in the Internet of Things, in particular to a low-error positioning algorithm aiming at the weighted improvement of the DV-Hop positioning algorithm. Background technique [0002] In a wireless sensor network, in order to ensure the reliability of information transmission, a wireless positioning algorithm with a very low positioning error is often needed to accurately locate the wireless collection nodes. In the wireless sensor network, the low-error positioning algorithm is based on the existing DV-Hop algorithm and obtains the minimum hop distance through known node position information. Then the reciprocal of the minimum hop distance is weighted to locate the wireless node. [0003] In the DV-Hop algorithm, its main positioning process is as follows: [0004] (A) Through a typical distance vector exchange protocol, each reference node in the network propagates its own locat...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04W64/00G01S5/02
CPCG01S5/0257H04W64/006
Inventor 倪雅琦王电钢毛启均杨洁陈龙潘可佳
Owner INFORMATION & TELECOMM COMPANY SICHUAN ELECTRIC POWER
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