Abstract
The accuracy and frequency of localization in wireless sensor networks play a crucial role in tracking and monitoring. Therefore, the study of high-efficient localization algorithm for accurate tracking is necessary. Through analyzing the traditional positioning based on Bayesian estimate process, the independent positioning of mobile node utilizing sampled sequential Monte Carlo algorithm was discussed. The application of Monte Carlo algorithm in positioning of wireless sensor networks was developed. This method has higher precision and does not need prior awareness of the wireless sensor networks and assumptions of node mobility. The algorithm maintains set of samples representing possible locations, achieves accurate localization cheaply with low seed density. Theoretical analysis and simulation experiments prove that Monte Carlo algorithm improves the positioning efficiency largely, utilizes sense information more effectively and decreases the impact of uncertainty. The properties of our technique were analyzed and experiment results from simulations were reported. The experiment results show that the sequential Monte Carlo localization technique can provide accurate localization.
| Original language | English |
|---|---|
| Pages (from-to) | 886-889 |
| Number of pages | 4 |
| Journal | Beijing Hangkong Hangtian Daxue Xuebao/Journal of Beijing University of Aeronautics and Astronautics |
| Volume | 33 |
| Issue number | 8 |
| Publication status | Published - Aug 2007 |
| Externally published | Yes |
Keywords
- Monte Carlo
- Node localization
- Sensor networks