Invention Grant
- Patent Title: Pedestrian adaptive zero-velocity update point selection method based on a neural network
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Application No.: US16816267Application Date: 2020-03-12
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Publication No.: US11519731B2Publication Date: 2022-12-06
- Inventor: Zhuoling Xiao , Xinguo Yu , Yi He , Bo Yan
- Applicant: University of Electronic Science and Technology of China
- Applicant Address: CN Chengdu
- Assignee: University of Electronic Science and Technology of China
- Current Assignee: University of Electronic Science and Technology of China
- Current Assignee Address: CN Chengdu
- Agency: Bayramoglu Law Offices LLC
- Priority: CN201910876262.7 20190917
- Main IPC: G01C21/18
- IPC: G01C21/18 ; G01C25/00 ; G06N3/04

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.
Public/Granted literature
- US20210080261A1 PEDESTRIAN ADAPTIVE ZERO-VELOCITY UPDATE POINT SELECTION METHOD BASED ON A NEURAL NETWORK Public/Granted day:2021-03-18
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