3D indoor positioning method based on spectral clustering and weighted back-propagation neural network

A technology of backpropagation and neural network, applied in the field of 3D indoor positioning based on spectral clustering and weighted backpropagation neural network, can solve the problems of low positioning accuracy and no consideration of wireless channel correlation, etc., and achieve the goal of improving positioning accuracy Effect

Active Publication Date: 2018-02-23
XIDIAN UNIV
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Problems solved by technology

However, due to the lack of consideration of wireless channel correlation, the positioning accuracy is low
[0003] To sum up, the problem with the existing technology is that some existing indoor positioning technologies based on 3D scenes need to use expensive and co

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  • 3D indoor positioning method based on spectral clustering and weighted back-propagation neural network
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  • 3D indoor positioning method based on spectral clustering and weighted back-propagation neural network

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[0046] In order to make the object, technical solution and advantages of the present invention more clear, the present invention will be further described in detail below in conjunction with the examples. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0047] The present invention uses received signal strength values ​​to establish a fingerprint database to reduce device complexity, utilizes spectral clustering to cluster reference points according to the correlation of wireless channels, and adopts a weighted backpropagation neural network (BPNN) algorithm to improve positioning accuracy and reduce training time.

[0048] The application principle of the present invention will be described in detail below in conjunction with the accompanying drawings.

[0049] Such as figure 1 As shown, the 3D indoor positioning method based on spectral clustering and weighted backprop...

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Abstract

The invention belongs to the technical field of wireless communication and indoor positioning and discloses a 3D indoor positioning method based on a spectral clustering and weighted back-propagationneural network. The 3D indoor positioning method is divided into an offline phase and an online phase, wherein the offline phase comprises the steps of dividing a reference point into NC clusters by using spectral clustering, and training a back-propagation neural network model by using reception signal intensity and corresponding position information in each cluster; and the online phase comprises the steps of estimating the position of a to-be-detected point by adopting a weighted back-propagation neural network (BPNN) algorithm, determining a weight of fingerprint of the to-be-detected point in each cluster, obtaining NC coordinates by utilizing the NC trained BPNN models, and performing weighted estimation on the position of the o-be-detected point by using the NC coordinates. According to the 3D indoor positioning method disclosed by the invention, the equipment complexity and layout cost are reduced, high positioning accuracy and positioning stability are provided, and the training time is shortened.

Description

technical field [0001] The invention belongs to the technical field of wireless communication and indoor positioning, and in particular relates to a 3D indoor positioning method based on spectral clustering and weighted backpropagation neural network. Background technique [0002] In recent years, with the surge in demand for indoor positioning services, a large number of indoor positioning technologies have emerged. Meanwhile, with the dense deployment of network infrastructure in fifth-generation (5G) networks, for example, small cells and Wi-Fi access points, indoor positioning technology can utilize abundant anchor nodes to accurately track and estimate target locations. The current indoor positioning technology can be divided into two types: indoor positioning method based on geometry and indoor positioning method based on location fingerprint. However, only when there is only a line-of-sight (LOS) between the target point and the anchor node, the position of the targe...

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Application Information

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IPC IPC(8): G01C21/20G06K9/62G06N3/08
CPCG06N3/084G01C21/206G06F18/23213
Inventor 盛敏彭琳琳刘俊宇李建东张琰厚丹妮郑阳刘伟
Owner XIDIAN UNIV
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