Abstract
An information fusion algorithm based on a class of asynchronous multi-rate and multi-sensor system was presented, where measurements from each sensor may be randomly missed with a certain probability. The fused result was obtained in virtue of information fusion theory of asynchronous multi-rate sensors and the approach for fusing missing measurements based on synchronous single-rate sensor system. According to theoretical analysis, we built the synchronized single-rate system model for dynamic system of asynchronous multi-rate sensors. So the approach could be adopted in time varying system with asynchronous multi-rate sensors. By using the improved Kalman filter for state estimation and federal filter for information fusion, we gain the optimal estimation based on all the observations. Theoretical analysis and simulation results show the efficiency of the proposed algorithm comparing with others.
| Original language | English |
|---|---|
| Pages (from-to) | 271-274 |
| Number of pages | 4 |
| Journal | Huazhong Keji Daxue Xuebao (Ziran Kexue Ban)/Journal of Huazhong University of Science and Technology (Natural Science Edition) |
| Volume | 37 |
| Issue number | SUPPL. 1 |
| Publication status | Published - Aug 2009 |
| Externally published | Yes |
Keywords
- Asynchronous multi-rate
- Information fusion
- Kalman filtering
- Linear system
- Missing measurements
- Sensor
- Time varying system