Sequence unscented Kalman filtering algorithm

被引:3
|
作者
Li, Hui-ping [1 ]
Xu, De-min [1 ]
jun, Jiang Li [1 ]
Zhang, Fu-bin [1 ]
机构
[1] Northwestern Polytech Univ, Xian 710072, Shaanxi Prov, Peoples R China
关键词
D O I
10.1109/ICIEA.2008.4582743
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Unscented Kalman Filter (UKF) has been proved to be a superior alternative to the extended Kalman filter (EKF) when solving the nonlinear system in recent years. In order to improve the real-time of the UKF, A new kind of UKF called Sequence UKF is proposed in this paper. Like Rao-Blackwellised Unscented Kalman Filter (RBUKF) [4], it also deals with nonlinear stochastic discrete-time system with linear measurement equation, however it can decrease the computational complexity with the same filtering accuracy. This algorithm reduces the measurement vector to scalars in measurement-update of UKF by sequence method, so it can avoid inversing the covariance of measurement and reduce a great mount of computation bound. Special algorithm is deduced in this paper. The high performance of sequence UKF is verified by using Monte Carlo simulations.
引用
收藏
页码:1374 / 1378
页数:5
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