Confidence transfer distributed volume Kalman filtering cooperative positioning method

A technology of confidence transfer and Kalman filtering, applied in location-based services, wireless communications, electrical components, etc., can solve problems such as high computational complexity, high energy consumption, and large sensor resources

Active Publication Date: 2019-09-10
HENAN UNIVERSITY
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Problems solved by technology

The classic sum-product wireless network positioning algorithm uses a non-parametric confidence transfer strategy to realize cooperative positioning of agent nodes. In order to ensure better positioning accuracy, a large number of random sampling particles need to be applied, resulting in high computational complexity and also occupying a large number of sensors. resource
Since message passing between mobile nodes needs to send all particles representing position information, high communication overhead leads to high energy consumption, shortening the service life of sensors and b

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  • Confidence transfer distributed volume Kalman filtering cooperative positioning method
  • Confidence transfer distributed volume Kalman filtering cooperative positioning method
  • Confidence transfer distributed volume Kalman filtering cooperative positioning method

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Embodiment Construction

[0037] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0038] Such as figure 1 Shown, the present invention comprises the following steps:

[0039] (1) Construct a distributed mobile agent node cooperative positioning network model, initialize the network parameters, the number of confidence iterations, the known reference node position, and the prior information of the mobile agent node state satisfy the Gaussian distribution; first, initialize the network parameters, t=0 time , the set of known reference node p...

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Abstract

The invention discloses a distributed volume Kalman filtering cooperative positioning method based on confidence transfer. The method comprises the steps that the initial state of mobile agent nodes in a wireless sensor network meets Gaussian distribution, and the mobile agent nodes are cooperatively positioned and modeled into an edge posteriori distribution estimation problem of multivariable nodes in a time-varying factor graph; a Gaussian parameterization confidence transfer and reconstruction strategy and a distributed volume Kalman filtering method are proposed, the posteriori distribution of each variable node is calculated on the factor graph, and further a positioning result of each mobile agent node is obtained. According to the cooperative positioning method disclosed by the invention, only the Gaussian parameterization confidence coefficient needs to be transmitted between the adjacent agent nodes, the expansibility and robustness are good, the communication overhead and the calculation complexity are relatively low, and the overall network positioning precision and efficiency are improved.

Description

technical field [0001] The invention relates to the technical field of cooperative positioning of mobile nodes in a wireless sensor network, in particular to a distributed volumetric Kalman filter cooperative positioning method for confidence transfer. Background technique [0002] At present, under the background of the rapid development of unmanned navigation technology and mobile robot technology, the demand for location information is gradually increasing. The use of wireless sensor network cooperative positioning technology to realize mobile node positioning has received extensive attention and research from many scholars. The classic sum-product wireless network positioning algorithm uses a non-parametric confidence transfer strategy to realize cooperative positioning of agent nodes. In order to ensure better positioning accuracy, a large number of random sampling particles need to be applied, resulting in high computational complexity and also occupying a large number ...

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Application Information

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IPC IPC(8): H04W4/02H04W64/00H04W84/18
CPCH04W4/023H04W64/003H04W84/18
Inventor 胡振涛付春玲代宝李军伟金勇周林魏倩
Owner HENAN UNIVERSITY
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