Please use this identifier to cite or link to this item: http://buratest.brunel.ac.uk/handle/2438/12662
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dc.contributor.authorSingh, AK-
dc.contributor.authorBhaumik, S-
dc.contributor.authorDate, P-
dc.date.accessioned2016-05-23T10:19:23Z-
dc.date.available2016-05-
dc.date.available2016-05-23T10:19:23Z-
dc.date.issued2016-
dc.identifier.citationApplied Mathematical Modelling, 40(19-20), (2016)en_US
dc.identifier.issn0307-904X-
dc.identifier.urihttp://www.sciencedirect.com/science/article/pii/S0307904X16302177-
dc.identifier.urihttp://bura.brunel.ac.uk/handle/2438/12662-
dc.description.abstractIn this paper, two existing quadrature filters, viz., the Gauss–Hermite filter (GHF) and the sparse-grid Gauss–Hermite filter (SGHF) are extended to solve nonlinear filtering problems with one step randomly delayed measurements. The developed filters are applied to solve a maneuvering target tracking problem with one step randomly delayed measurements. Simulation results demonstrate the enhanced accuracy of the proposed delayed filters compared to the delayed cubature Kalman filter and delayed unscented Kalman filter.en_US
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.subjectNonlinear filteringen_US
dc.subjectRandomly delayed measurementsen_US
dc.subjectGauss–Hermite quadrature ruleen_US
dc.subjectProduct ruleen_US
dc.subjectSmolyak ruleen_US
dc.titleQuadrature filters for one-step randomly delayed measurementsen_US
dc.typeArticleen_US
dc.identifier.doihttp://dx.doi.org/10.1016/j.apm.2016.04.016-
dc.relation.isPartOfApplied Mathematical Modelling-
pubs.publication-statusPublished-
Appears in Collections:Dept of Mathematics Research Papers

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