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Bayesian Fault Detection Method for Linear Systems with Outliers

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Details

Original languageEnglish
Title of host publicationUbiquitous Positioning, Indoor Navigation and Location-Based Services, UPINLBS, 3-4 October 2012, Helsinki
Place of PublicationPiscataway, NJ
PublisherIEEE
Pages1-5
Number of pages5
ISBN (Electronic)978-1-4673-1909-6
ISBN (Print)978-1-4673-1908-9
DOIs
Publication statusPublished - 2012
Publication typeA4 Article in a conference publication

Publication series

NameUbiquitous Positioning, Indoor Navigation and Location-Based Services

Abstract

A novel approach for monitoring the accuracy of the Bayesian estimate of linear Gaussian state-space model is introduced, based on the monitoring of the propagation of the errors in the Kalman filter algorithm. The effect of the sensor errors on the Kalman filter estimate is explicitly computed and compensated for. Marginalized particle filter is used to compute the posterior distribution of the sensor errors and using a target tracking simulation it is shown that the proposed method has improved performance over the standard DIA method

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