Abstract
To improve the performance of MEMES IMU based integrated system, the data fusion method integrated AI and Kalman filter was discussed. First, GPS signal validity and vehicle motion status were identified by using fuzzy logics. And when GPS doesn't outage, its data were set higher weight to be used to guide ALV; otherwise, AI (Artificial Intelligence) based integration algorithm with the help of Kalman filter was adopted. The method can make full use of the advantages of KF (Kalman Filter) and AI, and reduce their limitations.
| Original language | English |
|---|---|
| Pages | 80-84 |
| Number of pages | 5 |
| DOIs | |
| Publication status | Published - 2006 |
| Event | 2006 IEEE International Conference on Information Acquisition, ICIA 2006 - Weihai, Shandong, China Duration: 20 Aug 2006 → 23 Aug 2006 |
Conference
| Conference | 2006 IEEE International Conference on Information Acquisition, ICIA 2006 |
|---|---|
| Country/Territory | China |
| City | Weihai, Shandong |
| Period | 20/08/06 → 23/08/06 |
Keywords
- ALV
- Artificial intelligence
- Dead-reckoning
- Kalman filter
- MEMS IMU/GPS
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Wang, M. (2006). Data fusion of MEMS IMU/GPS integrated system for autonomous land vehicle. 80-84. Paper presented at 2006 IEEE International Conference on Information Acquisition, ICIA 2006, Weihai, Shandong, China. https://doi.org/10.1109/ICIA.2006.305846