WSN (wireless sensor network) indoor positioning method based on hidden markov models

A technology for indoor positioning and modeling, which is used in electrical components, wireless communication, network topology, etc.

Inactive Publication Date: 2013-10-02
NANCHANG HANGKONG UNIVERSITY
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  • Abstract
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  • Application Information

AI Technical Summary

Problems solved by technology

However, the use of self-organized WSN network for indoor positioning has problems such as: the link quality is not reliable enough, the surrounding environment is noisy, and the final result of the received positioning is jittery.

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  • WSN (wireless sensor network) indoor positioning method based on hidden markov models
  • WSN (wireless sensor network) indoor positioning method based on hidden markov models
  • WSN (wireless sensor network) indoor positioning method based on hidden markov models

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Embodiment Construction

[0036] The following combination figure 1 , figure 2 , image 3 , Figure 4 Further illustrate the WSN indoor positioning method based on Hidden Markov Model of the present invention, its specific steps are as follows:

[0037] Training process:

[0038]Step 1: According to the accuracy requirements for positioning nodes, divide the indoor area that needs to be positioned into grids. The size of each grid determines the required positioning accuracy of the positioned nodes. The positioning accuracy of nodes refers to the positioning accuracy. The distance deviation between the output node position and its actual position. The positioning accuracy of the nodes is selected according to actual requirements. The positioning accuracy of the general indoor nodes can be selected as 2 meters, that is to say, the distance between the located nodes and their actual positions is within 2 meters. In the present invention, the grid The shape of the grid is preferably a square grid. ...

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Abstract

The invention discloses a WSN (wireless sensor network) indoor positioning method based on hidden markov models. The method is that an indoor positioning assembly program is additionally arranged in the system with the help of an existing deployed WSN indoor on the basis of not changing a network topology structure and system functions, distance related characteristic parameters of radio frequency of positioning mobile nodes indoor are collected, and the collected characteristic vectors are processed by using the hidden markov models, thereby overcoming influences of environment changes, man-made interferences and the like to obtain the precise location of the mobile nodes indoor. The steps are that an indoor area to be positioned is divided into grids, and the size of the grid is the required positioning precision; the characteristic value of the node is collected and pretreated firstly, then positioning calculation is carried out by using the trained hidden markov models, and finally the models output locating position information of the node indoor is outputted by the models.

Description

technical field [0001] The invention relates to the fields of wireless sensor network technology, artificial intelligence, pattern recognition, etc., and in particular to a WSN indoor positioning method based on a hidden Markov model. Background technique [0002] According to the "National Medium and Long-Term Science and Technology Development Plan (2006-2020) )), "National "Eleventh Five-Year" Science and Technology Development Plan" and "863 Program "Eleventh Five-Year" Development Outline" and other national science and technology strategic planning documents The field of earth observation and navigation technology is listed as a key frontier exploration topic. Among them, "high-precision seamless navigation and positioning technology" has become an important sub-topic in this field and has received extensive attention. For future mobile users, not only need to obtain open [0003] The location information in the wide environment, the demand for positioning informatio...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04W64/00H04W84/18
Inventor 丁新朗刘肇荣陈宇斌李越
Owner NANCHANG HANGKONG UNIVERSITY
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