Pedestrian adaptive zero-velocity update point selection method based on a neural network
US11519731B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Mar 12, 2020 |
| Grant date | Dec 6, 2022 |
| Priority date | — |
| Expiry date | Feb 27, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/0464
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
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.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.