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Multi-target orientation method of wireless sensor network based on probability weighting

A wireless sensor, multi-target positioning technology, applied in wireless communication, advanced technology, electrical components, etc., can solve the problems of increased information transmission in sensor networks, a large amount of computing and communication overhead, and a large impact on positioning accuracy, reducing information bandwidth. , the effect of saving energy consumption and reducing energy consumption

Inactive Publication Date: 2009-06-24
SHANGHAI JIAO TONG UNIV +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, both methods have the limitation of ranging technology. The ranging error has a great influence on the positioning accuracy, and at the same time, a large amount of calculation and communication overhead are required.
Moreover, when the number of positioned targets increases, it will also lead to a large increase in the transmission information within the sensor network, and the bandwidth requirements will also increase accordingly.

Method used

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  • Multi-target orientation method of wireless sensor network based on probability weighting
  • Multi-target orientation method of wireless sensor network based on probability weighting
  • Multi-target orientation method of wireless sensor network based on probability weighting

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0029] Such as figure 1 As shown, this embodiment includes the following steps:

[0030] The first step is to divide the 60cm×60cm plane area with known coordinates into a grid of 60×60, such as figure 2 As shown, let 13 indifferent sensors S 1 ~S 13 Evenly distributed in the order of rows and columns in the area, such as image 3 As shown by the black dot in the middle, this area is fully covered, and the coverage of a single sensor is approximately a circle with a radius of R=50cm, and the error is R e =R / 3;

[0031] In the second step, according to the distance between the grid and the sensor nodes, establish a probability weighted model that the grid is covered by the sensor nodes: define the sensor node S i The coordinates S(x i ,y i ), where 1≤i≤13, defines the grid coordinates P(x, y), defines the grid to the sensor node S i distance d ( S i , P ) ...

Embodiment 2

[0039] Such as figure 1 As shown, this embodiment includes the following steps:

[0040] The first step is to divide the 60cm×60cm plane area with known coordinates into a grid of 100×100, such as figure 2 As shown, let 13 indifferent sensors S 1 ~S 13 Evenly distributed in the order of rows and columns in the area, such as image 3 As shown, so that the area is fully covered, the coverage of a single sensor is approximately a circle with a radius of R = 50cm, and the error is R e =R / 3;

[0041] In the second step, according to the distance between the grid and the sensor nodes, establish a probability weighted model that the grid is covered by the sensor nodes: define the sensor node S i The coordinates S(x i ,y i ), where 1≤i≤13, defines the grid coordinates P(x, y), defines the grid to the sensor node S i distance d ( S i , P ) = ...

Embodiment 3

[0049] Such as figure 1 As shown, this embodiment includes the following steps:

[0050] Step 1: Divide the 60cm×60cm plane area with known coordinates into a grid of 200×200, such as figure 2 As shown, let 13 indifferent sensors S 1 ~S 13 Evenly distributed in the order of rows and columns in the area, such as image 3 As shown, so that the area is fully covered, the coverage of a single sensor is approximately a circle with a radius of R = 50cm, and the error is R e =R / 3;

[0051] The second step: according to the distance between the grid and the sensor node, establish a probability weighted model that the grid is covered by the sensor node: define the sensor node S i The coordinates S(x i ,y i ), where 1≤i≤13, defines the grid coordinates P(x, y), defines the grid to the sensor node S i distance d ( S i , P ) = ...

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Abstract

Disclosed is a multiple objective positioning method based on the probability weight in the wireless sensor network, which belongs to the wireless communication technology field. In the invention, gridding division is carried out on the plane area in which the sensor network is distributed, and a gridding probability weight model is established according to the relative position of the gridding and sensor nodes; the sensor nodes detect the objective and gives a certain weight to each gridding according to the probability weight model; and each gridding can sum up the weights given to the gridding by different sensor nodes; the summation of the weights exceeds a gridding coordinate with the certain threshold, namely the objective coordinate, so as to realize the objective positioning. The method avoids the problem of the accumulated error commonly seen in the distributed-type multiple objective positioning, improves the performance of the multiple objective positioning, saves the energy consumption, and correspondingly reduces the requirements for sensor devices.

Description

technical field [0001] The invention relates to a method in the technical field of wireless communication, in particular to a multi-target positioning method based on probability weighting in a wireless sensor network. Background technique [0002] In wireless sensor networks, wireless sensors are often placed artificially in different environments to perform various monitoring tasks. Among them, the research on target positioning mostly adopts the same method as the sensor itself, which can be divided into two categories: distance measurement technology-based methods and methods without ranging techniques. The former measures the point-to-point distance or angle information between nodes, and uses trilateration, triangulation or maximum likelihood estimation to calculate the node position. This method has high node positioning accuracy and can be reduced by various methods. The impact of ranging error on positioning, but requires a lot of computing and communication overhe...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04W64/00H04W88/18
CPCY02B60/50Y02D30/70
Inventor 徐昌庆徐建良楼财义裴智强查希
Owner SHANGHAI JIAO TONG UNIV