A Variational Bayesian algorithm for Extended Target Tracking with Unknown Measurement Noise

被引：0
|
作者：
Ma, Tianli [1 ]
Wang, Yan [1 ]
Chen, Chaobo [1 ]
Cao, Kai [1 ]
机构：
[1] Xian Technol Univ, Sch Elect Informat Engn, Xian 710021, Peoples R China
来源：
PROCEEDINGS OF THE 38TH CHINESE CONTROL CONFERENCE (CCC) | 2019年
关键词：
EOT; Student-t distribution; Variational Bayesian; Heavy-tailed distribution; ROBUST; OBJECT;
D O I：
10.23919/chicc.2019.8866366
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The problem of extended target tracking in an unknown non-Gaussian noise field is considered. A Student-t distribution is used to model the measurement noise statistics that combining the sensor error with the extended uncertainty. An improved variational Bayesian algorithm is proposed to estimate the system states and the parameters of the measurement noise. Simulation results show that the proposed method has improved the estimation performance of the extended target tracking system compared with the traditional approaches.
引用
收藏
页码：3385 / 3389
页数：5
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