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GNSS/INS Integration Based on Machine Learning LightGBM Model for Vehicle Navigation
Content Provider | MDPI |
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Author | Li, Bangxin Chen, Guangwu Si, Yongbo Zhou, Xin Li, Pengpeng Li, Peng Fadiji, Tobi |
Copyright Year | 2022 |
Description | To solve the problem of data accuracy degradation of vehicle GNSS/INS integrated navigation systems when the GNSS signal is unavailable or there is a GNSS outage, this paper improves the existing GNSS/INS integration methodology for land vehicle navigation based on the AI method. First, a GNSS/INS integration methodology for land vehicle navigation based on position update architecture (PUA) using LightGBM regression for predicting the position of a vehicle during a GNSS outage is presented. It uses LightGBM to model the relationship between INS data and vehicle position changes. On-board INS and GNSS data are collected when the GNSS signal is available and are used to train the PUA-LightGBM model; in the event of a GNSS outage, INS data are used as the input to the PUA-LightGBM to predict the change in vehicle position. Second, a vehicle navigation data acquisition system was designed for model validation. This included a self-developed GNSS/INS integrated navigation system and a Novatel pwrpak7-e1 GNSS/INS integrated navigation system for data acquisition on six road segments. Finally, the collected data were used for machine learning training of the PUA-LightGBM model and the existing PUA-RandomForest model. As a result, the PUA-LightGBM predicts the vehicle position with less error in the event of a GNSS outage and takes less time to train. It was also demonstrated that by allowing the model to be dynamically trained or updated while the vehicle is moving the PUA-LightGBM could adapt perfectly to the predictions of vehicle position changes in different complex road segments. |
Starting Page | 5565 |
e-ISSN | 20763417 |
DOI | 10.3390/app12115565 |
Journal | Applied Sciences |
Issue Number | 11 |
Volume Number | 12 |
Language | English |
Publisher | MDPI |
Publisher Date | 2022-05-30 |
Access Restriction | Open |
Subject Keyword | Applied Sciences Transportation Science and Technology Lightgbm Integrated Navigation Algorithm Global Navigation Satellite System Inertial Navigation System Gnss Outage |
Content Type | Text |
Resource Type | Article |