Two Modified Unscented Kalman Filter and Acceleration Information in Unmanned Surface Vehicle Estimation

被引：7
|
作者：
Ma, Yulong [1 ]
机构：
[1] Guilin Univ Technol, Coll Mech & Control Engn, Guilin 541004, Peoples R China
来源：
IFAC PAPERSONLINE | 2015年 / 48卷 / 28期
关键词：
diagonal similar decomposition; acceleration; singular value decomposition; positive semidefinite;
D O I：
10.1016/j.ifacol.2015.12.337
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 stability problem is one of the existing problems of unscented Kalman filter (UKF), which due to the nonlinearity and complexity of system. The precision will be decreased or even UKF will be halted when the algorithm can't ensure the state covariance to be positive semidefinite. Based on decomposition of state covariance, the paper first reviews two modified UKFs which can enhance the state covariance to be positive semidefinite, then describes a method which combines the modified UKFs with acceleration measurement together to unmanned surface vehicle (USV) state estimation which main advantage lies in binding UKF with acceleration to simplify the system estimation model, so that it becomes an online estimation algorithm with higher precision and lower calculation complexity. (C) 2015, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.
引用
收藏
页码：1450 / 1455
页数：6
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