NIRK-based accurate continuous–discrete extended Kalman filters for estimating continuous-time stochastic target tracking models

This paper presents three state estimators grounded in the variable-stepsize Gauss- and Lobatto-type Nested Implicit Runge–Kutta (NIRK) formulas of orders 4 and 6 and designed for treating continuous-time stochastic systems arisen in radar tracking. Our filters are built within the Extended Kalman F...

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Veröffentlicht in:	Journal of computational and applied mathematics Jg. 316; S. 260 - 270
Hauptverfasser:	Kulikova, M.V., Kulikov, G.Yu
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier B.V 15.05.2017
Schlagworte:	Accuracy Adaptive MDE solver with local and global error controls Automatic control Construction methods Continuous-time stochastic target tracking model Continuous–discrete stochastic system Estimators Extended Kalman filter Gauss- and Lobatto-type nested implicit Runge–Kutta formulas Mathematical models Matlab Mazzoni’s hybrid method Permissible error Radar tracking 65L05 93E11 Continuous-time stochastic target tracking model Mazzoni’s hybrid method Gauss- and Lobatto-type nested implicit Runge–Kutta formulas Continuous–discrete stochastic system Adaptive MDE solver with local and global error controls Extended Kalman filter
ISSN:	0377-0427, 1879-1778
Online-Zugang:	Volltext
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