| Bayesian target tracking based on particle filter |
| |
| 作者姓名： | 邓小龙 谢剑英 郭为忠 |
| |
| 作者单位： | Dept .of Automation，Shanghai Jiaotong Univ，Dept .of Automation，Shanghai Jiaotong Univ，Dept .of Mechanical Engineering，Shanghai Jiaotong Univ Shanghai 200030，P. R. China，Shanghai 200030，P. R. China，Shanghai 200030，P. R. China |
| |
| 基金项目： | This project was supported by the National Natural Science Foundation of China (50405017) . |
| |
| 摘 要： | 1 .INTRODUCTIONIn many fields including target tracking, robotics ,signal processing, ti me-series analysis , etc , theKal manfilter is one of the most widely used methodsfor esti mationinlinear Gaussiansystemand measure-ment models . However , the application of theKal man filter to nonlinear systems can be difficult .Most common approach is to use the extendedKal manfilter (EKF) .EKFsi mplylinearizes all non-linear models by using Taylor series expansions andcan, however , lead to p…
|
Bayesian target tracking based on particle filter |
| |
| Deng Xiaolong,Xie Jianying,Guo Weizhong.Bayesian target tracking based on particle filter[J].Journal of Systems Engineering and Electronics,2005,16(3). |
| |
| Authors: | Deng Xiaolong Xie Jianying Guo Weizhong |
| |
| Institution: | 1. Dept.of Automation,Shanghai Jiaotong Univ.,Shanghai 200030,P.R.China
2. Dept.of Mechanical Engineering,Shanghai Jiaotong Univ.,Shanghai 200030,P.R.China |
| |
| Abstract: | For being able to deal with the nonlinear or non Gaussian problems, particle filters have been studied by many researchers. Based on particle filter, the extended Kalman filter (EKF) proposal function is applied to Bayesian target tracking. Markov chain Monte Carlo (MCMC) method, the resampling step, etc novel techniques are also introduced into Bayesian target tracking. And the simulation results confirm the improved particle filter with these techniques outperforms the basic one. |
| |
| Keywords: | nonlinear/non Gaussian extended Kalman filter particle filter target tracking proposal function |
| 本文献已被 CNKI 万方数据 等数据库收录！ |
