Neural network geomagnetic positioning method based on multi-feature driving and computer equipment

The invention is suitable for the field of indoor positioning, and provides a neural network geomagnetic positioning method based on multi-feature driving, a computer readable storage medium and computer equipment. The method comprises the following steps: receiving geomagnetic signals and sensor in...

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Bibliographic Details
Main Authors YAN SUQING, LIANG WEIBIN, FU WENTAO, SU YALAN, XIAO JIANMING, JI YUANFA, ZHAO SONGKE, JIA QIANZI
Format Patent
LanguageChinese
English
Published 19.01.2024
Subjects
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
GYROSCOPIC INSTRUMENTS
MEASURING
MEASURING DISTANCES, LEVELS OR BEARINGS
NAVIGATION
PHOTOGRAMMETRY OR VIDEOGRAMMETRY
PHYSICS
SURVEYING
TESTING
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Summary:The invention is suitable for the field of indoor positioning, and provides a neural network geomagnetic positioning method based on multi-feature driving, a computer readable storage medium and computer equipment. The method comprises the following steps: receiving geomagnetic signals and sensor information collected by a mobile terminal, and creating a multi-dimensional data set for geomagnetic positioning and step length estimation; geomagnetic positioning estimation is carried out based on the ResNet-GRU-LSTM neural network model, and a predicted geomagnetic positioning result is obtained; obtaining a step length, a step frequency and a direction angle for predicting and obtaining pedestrian dead reckoning (PDR) positioning by using a hierarchical GRU neural network model; and according to the step length, the step frequency, the direction angle and the geomagnetic positioning result, performing geomagnetic auxiliary multi-feature driven PDR positioning through particle filtering to obtain the final posit
Bibliography:Application Number: CN202311353762