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An indoor positioning method and system

A technology for indoor positioning and to-be-located points, which is applied in the field of indoor positioning methods and systems, can solve problems such as large amount of calculation, low positioning efficiency, and inability to perform timely and accurate positioning, and achieves the effect of reducing the amount of calculation and improving the speed.

Active Publication Date: 2020-05-22
THE PLA INFORMATION ENG UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] In view of this, the present application provides an indoor positioning method and system to overcome the low positioning efficiency when performing indoor positioning in the prior art, and the inability to perform timely and accurate positioning due to the large amount of calculation when positioning in a large positioning site question

Method used

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  • An indoor positioning method and system
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  • An indoor positioning method and system

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Experimental program
Comparison scheme
Effect test

Embodiment 1

[0056] Embodiment 1 of the present application provides an indoor positioning method, such as figure 1 as shown, figure 1 It is a flow chart of an indoor positioning method provided in Embodiment 1 of the present application. The method includes:

[0057] S101: Obtain the feature value of the target point of the point to be located;

[0058] In this application, the eigenvalue can specifically be an RSS (Received Signal Strength, received signal strength) vector. First, in the indoor positioning area, there are not enough APs (Access Points) to cover the entire positioning area, and a mobile terminal is used to measure The RSS of each AP received by the point to be located is used as the characteristic value of the target point of the point to be located.

[0059] S102: Calculate the distance from the feature value of the target point to each cluster center to determine the cluster where the point to be located is located;

[0060] Among them, the cluster center is the cen...

Embodiment 2

[0067] On the basis of Embodiment 1, Embodiment 2 of the present application provides a more specific method for indoor positioning. The method includes as figure 1 Steps shown:

[0068] S101: Obtain the feature value of the target point of the point to be located;

[0069] In this application, the eigenvalue can specifically be an RSS (Received Signal Strength, received signal strength) vector. First, in the indoor positioning area, there are not enough APs (Access Points) to cover the entire positioning area, and a mobile terminal is used to measure The RSS of each AP received by the point to be located is used as the characteristic value of the target point of the point to be located.

[0070] S102: Calculate the distance from the feature value of the target point to each cluster center to determine the cluster where the point to be located is located;

[0071] Among them, the cluster center is the center of each cluster obtained by pre-optimizing the division of the pos...

Embodiment 3

[0097] On the basis of Embodiment 1, Embodiment 3 of the present application provides an indoor positioning system, such as image 3 as shown, image 3 It is a schematic structural diagram of an indoor positioning system provided in Embodiment 3 of the present application. The positioning system includes: a division unit 301, an acquisition unit 302, a calculation unit 303 and a matching unit 304, wherein,

[0098]A division unit 301, configured to optimally divide the positioning area corresponding to the point to be located to obtain multiple clusters;

[0099] In this application, the division unit first divides the positioning area into multiple clusters, and determines the cluster center of each cluster.

[0100] An acquisition unit 302, configured to acquire the target point feature value of the point to be located;

[0101] In this application, the eigenvalue can specifically be an RSS (Received Signal Strength, received signal strength) vector. First, in the indoor ...

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Abstract

The invention provides an indoor positioning method and system. The positioning method comprises the following steps: obtaining a target point characteristic value of a point to be positioned; calculating a distance from the target point characteristic value to each clustering center, so as to determine the cluster of the point to be positioned, wherein the clustering center is a center of each cluster, which is obtained by optimizing and dividing a positioning region corresponding to the point to be positioned in advance; matching the target point characteristic value with a fingerprint point characteristic value of the point to be positioned in the cluster, so as to determine the position of the point to be positioned. According to the positioning method, the positioning region is divided into the plurality of clusters through utilizing a simulated annealing clustering algorithm; a subspace, namely the cluster, of the point to be positioned is determined firstly, so that the calculation amount of an online matching phase is reduced and the positioning speed is improved.

Description

technical field [0001] The present application relates to the technical field of positioning, and more specifically, to an indoor positioning method and system. Background technique [0002] With the construction of a large number of indoor infrastructure, there are currently a series of large indoor places such as indoor parking lots, civil airports, and hospitals in China. This makes people's demand for indoor security and location services continue to increase. Scholars' research hotspots. [0003] At present, the fingerprint positioning algorithm has become the main positioning technology for indoor positioning, including the kNN (k-Nearest Neighbor, K nearest neighbor) neighbor algorithm and the K-weighted nearest neighbor method. The fingerprint positioning method first establishes the fingerprint database, and then matches the fingerprint database. The establishment of the fingerprint database is to collect the characteristic values ​​of each reference point in the ...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01C21/20
CPCG01C21/206
Inventor 王建辉张剑于宏毅张效义王大鸣刘洛琨朱义君张霞逯志宇侯文佐
Owner THE PLA INFORMATION ENG UNIV