Pedestrian adaptive zero-velocity update point selection method based on a neural network

Abstract

A pedestrian adaptive zero-velocity update point selection method based on a neural network, including the following steps: S1, collecting inertial navigation data of different pedestrians in different motion modes; S2, preprocessing the inertial navigation data collected in the step S1, labeling the preprocessed data, and obtaining a training data set, a validation data set, and a test data set according to the preprocessed data and a label corresponding to the preprocessed data; S3, inputting the training data set to a convolutional neural network for training, obtaining a pedestrian adaptive zero-velocity update point selection model based on the convolutional neural network, and using the validation data set to validate the pedestrian adaptive zero-velocity update point selection model; and S4, inputting the test data set into the pedestrian adaptive zero-velocity update point selection model based on the convolutional neural network, and obtaining a selection result of pedestrian zero-velocity update points.

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