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

来源：

ICIEA 2008: 3RD IEEE CONFERENCE ON INDUSTRIAL ELECTRONICS AND APPLICATIONS, PROCEEDINGS, VOLS 1-3 | 2008年

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

页码：1374 / 1378

页数：5

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