Abstract
A Gaussian sum particle filter using RBF Neural Network (BRF-GSPF) is proposed to deal with nonlinear sequential Bayesian estimation. The nonlinear non-Gaussian filtering and predictive distributions are approximated as weighted Gaussian mixtures, and mixtures components are gotten by RBF neural network. This method implements conveniently in parallel way by cancelling resampling that solves weight degeneracy in particle filter. The tracking performance of the RBF-GSPF is evaluated and compared to the particle filter (PF) via simulations with heavy-tailed glint measurement noise. It is shown that the RBF-GSPF improves tracking precise and has strong adaptability.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the 7th World Congress on Intelligent Control and Automation, WCICA'08 |
| Pages | 3071-3076 |
| Number of pages | 6 |
| DOIs | |
| Publication status | Published - 2008 |
| Event | 7th World Congress on Intelligent Control and Automation, WCICA'08 - Chongqing, China Duration: 25 Jun 2008 → 27 Jun 2008 |
Publication series
| Name | Proceedings of the World Congress on Intelligent Control and Automation (WCICA) |
|---|
Conference
| Conference | 7th World Congress on Intelligent Control and Automation, WCICA'08 |
|---|---|
| Country/Territory | China |
| City | Chongqing |
| Period | 25/06/08 → 27/06/08 |
Keywords
- Gaussian mixture
- Gaussian particle filter
- Gaussian sum particle filter
- Particle filters
- RBF neural network
Fingerprint
Dive into the research topics of 'Gaussian sum particle filtering based on RBF neural networks'. Together they form a unique fingerprint.Cite this
Fan, G., Dai, Y., & Wang, H. (2008). Gaussian sum particle filtering based on RBF neural networks. In Proceedings of the 7th World Congress on Intelligent Control and Automation, WCICA'08 (pp. 3071-3076). Article 4593412 (Proceedings of the World Congress on Intelligent Control and Automation (WCICA)). https://doi.org/10.1109/WCICA.2008.4593412