Abstract
On the basis of the filtering algorithm of target tracking, the data fusion algorithm adopting fuzzy theory was proposed. By use of fuzzy theories, the feature extraction was made for the filter data from two sensors and then the fuzzy illation was done under certain subordinate functions and rules, thereby a coefficient was got to adjust the acceleration square variance automatically in order to keep the rapid response to the practical conditions, in addition, the Monte Carlo simulation methods were used to compare the results obtained before and after the data fusion algorithm was applied. The fuzzy algorithm fully makes use of the relative knowledge extracted from the experts in the field, the feedback of the fusion results to the single sensor can enhance the single sensor's precision.
| Original language | English |
|---|---|
| Pages (from-to) | 343-346 |
| Number of pages | 4 |
| Journal | Beijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology |
| Volume | 20 |
| Issue number | 3 |
| Publication status | Published - 2000 |
Keywords
- Fuzzy illation
- Fuzzy rules
- Kalman filtering
- Subordinate function