Show simple item record

dc.contributor.authorKim, Du Yong
dc.contributor.authorLee, S.
dc.contributor.authorJeon, M.
dc.identifier.citationKim, D.Y. and Lee, S. and Jeon, M. 2011. Outlier rejection methods for robust Kalman filtering, pp. 316-322.

In this paper we discuss efficient methods of the state estimation which are robust against unknown outlier measurements. Unlike existing Kalman filters, we relax the Gaussian assumption of noises to allow sparse outliers. By doing so spikes in channels, sensor failures, or intentional jamming can be effectively avoided in practical applications. Two approaches are suggested: median absolute deviation (MAD) and L 1 -norm regularized least squares (L 1 -LS). Through a numerical example two methods are tested and compared. © 2011 Springer-Verlag.

dc.titleOutlier rejection methods for robust Kalman filtering
dc.typeConference Paper
dcterms.source.volume184 CCIS
dcterms.source.titleCommunications in Computer and Information Science
dcterms.source.seriesCommunications in Computer and Information Science
curtin.departmentDepartment of Electrical and Computer Engineering
curtin.accessStatusFulltext not available

Files in this item


There are no files associated with this item.

This item appears in the following Collection(s)

Show simple item record