Please use this identifier to cite or link to this item: http://buratest.brunel.ac.uk/handle/2438/12191
Full metadata record
DC FieldValueLanguage
dc.contributor.authorDate, P-
dc.contributor.authorSingh, AK-
dc.contributor.authorBhoumik, S-
dc.date.accessioned2016-02-25T13:52:23Z-
dc.date.available2016-02-25T13:52:23Z-
dc.date.issued2015-
dc.identifier.citationIEEE Transactions on Automatic Control, (99), (2016)en_US
dc.identifier.issn0018-9286-
dc.identifier.urihttp://ieeexplore.ieee.org/search/searchresult.jsp?newsearch=true&queryText=A%20Modified%20Bayesian%20Filter%20for%20Randomly%20Delayed%20Measurements-
dc.identifier.urihttp://bura.brunel.ac.uk/handle/2438/12191-
dc.description.abstractThe traditional Bayesian approximation framework for filtering in discrete time systems assumes that the measurement is available at every time instant. But in practice, the measurements could be randomly delayed. In the literature, the problem has been examined and solution is provided by restricting the maximum number of delay to one or two time steps. This paper develops an approach to deal with the filtering problems with an arbitrary number of delays in measurement. Pursuing this objective, traditional Bayesian approximation to nonlinear filtering problem is modified by reformulating the expressions of mean and covariances which appear during the measurement update. We use the cubature quadrature rule to evaluate the multivariate integral expressions for the mean vector and the covariance matrix which appear in the developed filtering algorithm. We compare the new algorithm which accounts for delay with the existing CQKF heuristics on two different examples and demonstrate how accounting for a random delay improves the filtering performance.en_US
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineersen_US
dc.subjectNonlinear filteringen_US
dc.subjectBayesian framwork of filteringen_US
dc.subjectRandom delay in measurementsen_US
dc.subjectCubature quadrature kalman filteren_US
dc.titleA modified bayesian filter for randomly delayed measurementsen_US
dc.typeArticleen_US
dc.identifier.doihttp://doi.dx.org/10.1109/TAC.2016.2531418-
dc.relation.isPartOfIEEE Trans Automatic Control-
pubs.publication-statusAccepted-
pubs.publication-statusAccepted-
Appears in Collections:Dept of Mathematics Research Papers

Files in This Item:
File Description SizeFormat 
Fulltext.pdf367.49 kBAdobe PDFView/Open


Items in BURA are protected by copyright, with all rights reserved, unless otherwise indicated.