Geomagnetic Indoor Localization Method Based on Gated Recurrent Neural Network and Particle Filter

A technology of cyclic neural network and particle filter, which is applied in ground navigation, instruments, navigation and other directions, can solve the problems of poor geomagnetic matching and positioning, low resolution of geomagnetic, etc., achieve good real-time positioning accuracy, good positioning accuracy, and reduce real-time calculation volume effect

Active Publication Date: 2022-04-01
HANGZHOU DIANZI UNIV
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Problems solved by technology

However, geomagnetism has the defect of low resolution, and geomagnetic signals will appear similar in different positions in the indoor environment, so the effect of geomagnetic matching and positioning is often not good

Method used

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  • Geomagnetic Indoor Localization Method Based on Gated Recurrent Neural Network and Particle Filter
  • Geomagnetic Indoor Localization Method Based on Gated Recurrent Neural Network and Particle Filter
  • Geomagnetic Indoor Localization Method Based on Gated Recurrent Neural Network and Particle Filter

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Embodiment Construction

[0025] The present invention will be described in detail below in combination with specific embodiments.

[0026] The invention mainly utilizes the gated cyclic neural network to extract the features of the geomagnetic track signal, and proposes a real-time geomagnetic positioning method combined with particle filtering on the basis of the gated cyclic neural network matching and positioning. Roughly framed as figure 1 shown. Specifically follow the steps below to implement.

[0027] Step 1. Construction of indoor geomagnetic map database:

[0028] The geomagnetic signal collected by the geomagnetic sensor is composed of three-dimensional vector x ,M y ,M z > Indicates that the three vector values ​​represent the geomagnetic signals measured on the three direction axes of the sensor respectively. In addition, the geomagnetic intensity signal is represented by the second-order norm of the three vector values. The geomagnetic intensity signal M is as follows:

[0029] ...

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Abstract

The invention discloses a geomagnetic indoor positioning method based on a gated cyclic neural network and a particle filter. In the invention, the geomagnetic indoor database is trained to perform the matching and positioning of the geomagnetic track signal by training the gated cyclic neural network. Using a well-trained gated recurrent neural network for matching and positioning can bring better positioning accuracy to the matching and positioning of geomagnetic trajectory signals. In addition, compared with the commonly used geomagnetic trajectory signal matching algorithm based on dynamic time planning, the trained model The amount of real-time calculation is reduced in the process of matching and positioning. The invention designs a system for real-time positioning based on a neural network model for matching and positioning geomagnetic track signals, combined with a particle filter algorithm. The system effectively utilizes the advantages of the gated recurrent neural network to extract the characteristics of the geomagnetic trajectory signal, and brings better real-time positioning accuracy to the particle filter algorithm.

Description

technical field [0001] The invention belongs to the field of indoor positioning, and in particular relates to a method for geomagnetic matching positioning based on a gated cyclic neural network, and a method for real-time positioning combined with particle filtering. Background technique [0002] Indoor positioning technology has broad application value in daily life, such as positioning in shopping malls, navigation in parking lots, etc. As a common indoor signal, geomagnetism has no infrastructure and has the characteristics of unique signal strength in different locations. However, geomagnetism has the defect of low resolution, and geomagnetic signals will appear similar in different positions in the indoor environment, so the effect of geomagnetic matching and positioning is often not good. The commonly used geomagnetic matching positioning algorithm mainly collects continuous geomagnetic trajectory signals and dynamic time planning algorithm to perform matching positi...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01C21/08G01C21/20
CPCG01C21/08G01C21/206
Inventor 颜成钢巩鹏博郑锦凯孙垚棋张继勇张勇东
Owner HANGZHOU DIANZI UNIV
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