Abstract
In this paper, we analyse an algorithm of target tracking based on neural network data fusion, explain that the traditional fusion algorithm has some shortcomings such as heavy calculation burden and the difficult selection of target vectors of neural network, and present a simplified algorithm. The theoretical analysis and Monte Carlo simulation methods are used to compare the traditional fusion algorithm with the new one. The simplified algorithm is more simple in principle, ess in data, faster in processing and less in error. It is suitable for the multisensors. The feedback of the fusion result to the single sensor can enhance the single sensor's precision.
| Original language | English |
|---|---|
| Pages (from-to) | 82-84 |
| Number of pages | 3 |
| Journal | Xi Tong Gong Cheng Yu Dian Zi Ji Shu/Systems Engineering and Electronics |
| Volume | 23 |
| Issue number | 3 |
| Publication status | Published - Mar 2001 |
Keywords
- Algorithm
- Kalman filtering
- Neural network
- Target tracking