@inproceedings{5bdbed4931e643d5bbc266ae24a9b0e7,
title = "Sequence unscented Kalman filtering algorithm",
abstract = "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.",
author = "Li, {Hui Ping} and Xu, {De Min} and Jiang, {Li Jun} and Zhang, {Fu Bin}",
year = "2008",
doi = "10.1109/ICIEA.2008.4582743",
language = "英语",
isbn = "9781424417186",
series = "2008 3rd IEEE Conference on Industrial Electronics and Applications, ICIEA 2008",
pages = "1374--1378",
booktitle = "2008 3rd IEEE Conference on Industrial Electronics and Applications, ICIEA 2008",
note = "2008 3rd IEEE Conference on Industrial Electronics and Applications, ICIEA 2008 ; Conference date: 03-06-2008 Through 05-06-2008",
}