Strong tracking filtering algorithm of randomly delayed measurements for nonlinear systems
type: Item
instance of: scholarly article
title: Strong tracking filtering algorithm of randomly delayed measurements for nonlinear systems
zbMATH Open document ID: 1394.93335
DOI: 10.1155/2015/869482
author: Hongtao Yang
author: Huibin Gao
author: Xin Liu
published in: Mathematical Problems in Engineering
publication date: 2018-08-27T00:00:00Z
review text: Summary: This paper focuses on the filtering problems of nonlinear discrete-time stochastic dynamic systems, such as the model simplification, noise characteristics uncertainty, initial conditions uncertainty, or system parametric variation. Under these circumstances, the measurements of system have one sampling time random delay. A new method, that is, strong tracking filtering algorithm of randomly delayed measurements (STF/RDM) for nonlinear systems based on recursive operating by analytical computation and first-order linear approximations, is proposed; a principle of extended orthogonality is presented as a criterion of designing the STF/RDM, and through the residuals between available and predicted measurements, the formula of fading factor is obtained. Under the premise of using the extended orthogonality principle, STF/RDM proposed in this paper can adjust the fading factor online via calculating the covariance of residuals, and then the gain matrices of the STF/RDM adjust in real time to enhance the performance of the proposed method. Lastly, in order to prove that the performance of STF/RDM precedes existing EKF method, the experiment of tracking maneuvering aircraft is carried out.
Mathematics Subject Classification ID: 93E11
Mathematics Subject Classification ID: 62M20
zbMATH DE Number: 6927434
Wikidata QID: Q59119719
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1155/2015/869482
OpenAlex ID: W2137906676
cites work: Advanced point-mass method for nonlinear state estimation
cites work: Generalised particle filters with Gaussian mixtures
cites work: New developments in state estimation for nonlinear systems
cites work: A new method for the nonlinear transformation of means and covariances in filters and estimators
cites work: Cubature Kalman Filters
cites work: Strong tracking filtering of nonlinear time-varying stochastic systems with coloured noise: application to parameter estimation and empirical robustness analysis
cites work: Extended and unscented filtering algorithms using one-step randomly delayed observations
cites work: Unscented filtering algorithm using two-step randomly delayed observations in nonlinear systems
cites work: Recursive estimation of discrete-time signals from nonlinear randomly delayed observations
cites work: Gaussian filter for nonlinear systems with one-step randomly delayed measurements
cites work: A sequential failure detection technique and its application
description: scientific article; zbMATH DE number 6927434