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Fusion representation network model training method, fingerprint representation method and equipment thereof

A network model and training method technology, applied in the field of positioning, can solve the problems of staying in feature combination or screening, etc., to achieve the effect of improving positioning accuracy, accurate positioning results, and improving feature discrimination

Active Publication Date: 2021-09-03
BEIJING UNIV OF POSTS & TELECOMM
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, most of the heterogeneous and heterogeneous feature fusion algorithms in the existing fusion positioning system still stay on feature combination or screening, and it is difficult to fundamentally change the problem of insufficient discrimination of fingerprint features

Method used

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  • Fusion representation network model training method, fingerprint representation method and equipment thereof
  • Fusion representation network model training method, fingerprint representation method and equipment thereof
  • Fusion representation network model training method, fingerprint representation method and equipment thereof

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Embodiment Construction

[0046] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention more clear, the embodiments of the present invention will be further described in detail below in conjunction with the accompanying drawings. Here, the exemplary embodiments and descriptions of the present invention are used to explain the present invention, but not to limit the present invention.

[0047] Aiming at the problems of low feature precision and insufficient completeness of a single positioning source in a complex indoor environment, and the difficulty of changing the feature discrimination degree of current fusion algorithms, the inventors of the present invention consider that there is a certain complementarity between CSI (Channel State Information) and image positioning. Fusion data can enrich positioning information. Multi-source fusion positioning can effectively alleviate the problems of low feature accuracy and insufficient completeness of sin...

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Abstract

The invention provides a fusion representation network model training method, a fingerprint representation method and equipment thereof, and the training method comprises the steps: carrying out the feature extraction of channel state information data through a multi-layer perceptron network, and obtaining a channel state information feature map; performing feature extraction on the image data of each orientation by using a convolutional neural network with the same weight to obtain a feature map of the image of each orientation; fusing the feature maps of the images of all orientations of the same training sample to obtain a multi-azimuth feature map; splicing the channel state information feature map and the multi-azimuth feature map to construct fusion representation; correspondingly constructing a fusion fingerprint database by using the channel state information and the fusion representation of the image, and performing parameter optimization by using a set measurement index to obtain a fusion representation network model; and setting a measurement index for measuring the distance between the feature fingerprints in the fusion fingerprint database. Through the scheme, the feature distinction degree can be improved, and the positioning accuracy is improved.

Description

technical field [0001] The invention relates to the field of positioning technology, in particular to a fusion representation network model training method, a fingerprint representation method and a device thereof. Background technique [0002] With the development of informatization and intelligence in society, information such as navigation and positioning occupy an increasing proportion in daily life, and the location-based service industry has been widely used in various fields. [0003] For complex indoor environments, a variety of positioning methods have been proposed. According to the signal source, they can be divided into positioning technologies based on wireless fidelity (Wireless-Fidelity, Wi-Fi), Bluetooth, ultra-wideband and other radio signals, and positioning technologies based on infrared, Positioning techniques for non-radio signals such as ultrasonic, visual and inertial systems. [0004] Among the many positioning sources, Wi-Fi and visual signal source...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06K9/62G06N3/04G06N3/08
CPCG06N3/08G06N3/045G06F18/213
Inventor 刘雯邓中亮陈宏
Owner BEIJING UNIV OF POSTS & TELECOMM
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