Indoor positioning method of inertial navigation based on bp neural network

A BP neural network and indoor positioning technology, applied in the field of indoor positioning, can solve problems such as low acceleration accuracy and rapid accumulation of inertial navigation positioning errors, and achieve the effects of improving accuracy, improving positioning accuracy, and reducing measurement noise

Active Publication Date: 2021-02-26
YANSHAN UNIV
View PDF7 Cites 1 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The currently used strapdown inertial navigation system uses acceleration data integration to obtain the step length. Since the acceleration measured by MEMS is not high in accuracy, the inertial navigation positioning error will accumulate rapidly.

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Indoor positioning method of inertial navigation based on bp neural network
  • Indoor positioning method of inertial navigation based on bp neural network
  • Indoor positioning method of inertial navigation based on bp neural network

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0022] In order to make the purpose, method and advantages of the embodiments of the present invention more clear, the BP neural network-based inertial navigation indoor positioning method of the present invention will be further described below in conjunction with the accompanying drawings.

[0023] The present invention is described by taking a positioning person wearing an ankle wearable device and walking indoors as a specific example, using the wearable device's internal three-axis acceleration sensor, three-axis angular velocity sensor and three-axis magnetometer to record the data of the person's walking for indoor positioning. Such as figure 1 As shown, the inertial navigation indoor positioning method based on BP neural network of the present invention comprises motion data acquisition and preprocessing stage, off-line training stage and real-time positioning stage:

[0024] 1. Data acquisition and preprocessing stage, including the following specific steps:

[0025]...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention discloses an inertial navigation indoor positioning method based on BP neural network, which includes a motion data collection and preprocessing stage, an off-line training stage and a real-time positioning stage. Data collection is through the left and right ankle wearable devices to collect the movement data of the personnel's two ankles, the personnel's height and step length; the data preprocessing is to use multi-sensor information fusion processing to obtain 7 neural network input data - left and right legs Attitude angle changes θ1 and θ2, ankle acceleration average, variance variance, left and right foot step duration time1 and time2, and height stature; the offline training phase includes: establishing a neural network step size estimation model; 7 input data and step length data input into the neural network for training; the real-time positioning stage includes: step recognition inside the right ankle wearable device, real-time prediction of step length, and real-time positioning through dead reckoning using step length and direction angle. The invention improves the accuracy and real-time performance of indoor positioning, and enhances the reliability.

Description

technical field [0001] The invention relates to the field of indoor positioning, in particular to a BP neural network-based inertial navigation indoor positioning method. Background technique [0002] Existing indoor positioning technology solutions mainly include Wi-Fi positioning technology, infrared positioning technology, ultrasonic positioning technology, visible light positioning technology, UWB technology, ZigBee technology, radio frequency tag identification technology, and computer vision positioning technology. Because these technologies need to build equipment for auxiliary positioning, the higher the positioning accuracy, the more the number of auxiliary equipment is required, so these technologies are not universally applicable and fast. Wi-Fi positioning technology needs to estimate the location of the receiver by setting up a Wi-Fi network indoors. Visible light positioning technology needs to clarify the position of the visible light source in advance. If th...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Patents(China)
IPC IPC(8): G01C21/20G01C21/16
CPCG01C21/16G01C21/206
Inventor 童凯谢正威刘刚
Owner YANSHAN UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap