Design and implementation of Gaussian filter for nonlinear system with randomly delayed measurements and correlated noises

Xiaoxu Wang, Yan Liang, Quan Pan, Chunhui Zhao and Feng Yang

Applied Mathematics and Computation, 2014, vol. 232, issue C, 1011-1024

Abstract: In this paper, we focus on the nonlinear state estimation problem with both one-step randomly delayed measurements and correlated noises. Firstly, a general framework of Gaussian filter is designed under Gaussian assumption on the conditional density. Furthermore, the implementation of Gaussian filter is transformed into the computation of the nonlinear numerical integrals in the proposed framework. Secondly, a new cubature Kalman filtering (CKF) algorithm is developed on the basis of the spherical-radial cubature rule for approximating such nonlinear integrals. Finally, the performance of the modified CKF is verified by a numerical simulation example.

Keywords: Nonlinear system; Randomly delayed measurement; Correlated noises; Gaussian filter; CKF; Spherical-radial rule (search for similar items in EconPapers)
Date: 2014
References: View complete reference list from CitEc
Citations: View citations in EconPapers (4)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0096300314000071
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:apmaco:v:232:y:2014:i:c:p:1011-1024

DOI: 10.1016/j.amc.2013.12.168

Access Statistics for this article

Applied Mathematics and Computation is currently edited by Theodore Simos

More articles in Applied Mathematics and Computation from Elsevier
Bibliographic data for series maintained by Catherine Liu ().