Vehicle Localization by Optimally Weighted Use of Cross-Correlated MEMS Sensor Data
The Global Navigation Satellite System (GNSS) is widely utilized to accurately determine the position of a vehicle, but at present, the accuracy may be degraded depending on the radio wave reception conditions from the satellite. There are also growing concerns about cyber-attacks on GNSS. We have b...
| Main Author: | |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IFSA Publishing, S.L.
2023-07-01
|
| Series: | Sensors & Transducers |
| Subjects: | |
| Online Access: | https://sensorsportal.com/HTML/DIGEST/july_2023/Vol_261/P_3291.pdf |
| Summary: | The Global Navigation Satellite System (GNSS) is widely utilized to accurately determine the position of a vehicle, but at present, the accuracy may be degraded depending on the radio wave reception conditions from the satellite. There are also growing concerns about cyber-attacks on GNSS. We have been developing a method for estimating the position of a traveling vehicle using MEMS sensor data obtained from air pressure, acceleration, gyro, and geomagnetic sensors. In the current work, we set up an experimental environment to collect data at 50 Hz and implemented a running test on an actual road. Optimizing the weighting of each item of sensor information enabled us to obtain characteristics of the road that could not be captured in the past. In addition, the application of an extreme data elimination filter confirmed that the position estimation accuracy was improved on the order of sum-meter. |
|---|---|
| ISSN: | 2306-8515 1726-5479 |