Name
Title | ||
|---|---|---|
A Robust Fixed-Interval Smoother For Nonlinear Systems With Non-Stationary Heavy-Tailed State And Measurement Noises |
Abstract | ||
|---|---|---|
We propose a robust fixed-interval smoother for nonlinear systems with non-stationary heavy-tailed state and measurement noises, in which the state and measurement noises are modelled as Gaussian-Student's t mixture distributions. The variational Bayesian technique is utilized to deduce the smoother approximately. The standard cubature Kalman smoother (CKS) and the robust Gaussian approximate smoother (RGAS) with fixed scale matrices and dof parameters are two particular cases of the proposed smoother. Numerical simulation and target tracking example show the merits of the proposed smoother. (C) 2020 Elsevier B.V. All rights reserved. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1016/j.sigpro.2020.107898 | SIGNAL PROCESSING |
Keywords | DocType | Volume |
Fixed-interval smoother, Non-stationary noise, Bernoulli distribution, Variational Bayesian | Journal | 180 |
ISSN | Citations | PageRank |
0165-1684 | 1 | 0.35 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mingming Bai | 1 | 6 | 1.79 |
| Yulong Huang | 2 | 186 | 21.07 |
| Guangle Jia | 3 | 1 | 1.03 |
| Yonggang Zhang | 4 | 87 | 16.11 |