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Please use this identifier to cite or link to this item: https://dspace.iiti.ac.in/handle/123456789/11643
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dc.contributor.authorKumar, Guddu Sarojen_US
dc.contributor.authorRamabadran, Swaminathanen_US
dc.contributor.authorSingh, Abhinoy Kumaren_US
dc.date.accessioned2023-05-03T15:04:47Z-
dc.date.available2023-05-03T15:04:47Z-
dc.date.issued2022-
dc.identifier.citationKumar, G., Swaminathan, R., & Singh, A. K. (2022). High-degree cubature quadrature kalman filter with fractional delayed measurement. Paper presented at the INDICON 2022 - 2022 IEEE 19th India Council International Conference, doi:10.1109/INDICON56171.2022.10040169 Retrieved from www.scopus.comen_US
dc.identifier.otherEID(2-s2.0-85149198172)-
dc.identifier.urihttps://doi.org/10.1109/INDICON56171.2022.10040169-
dc.identifier.urihttps://dspace.iiti.ac.in/handle/123456789/11643-
dc.description.abstractGaussian filtering is a popular Bayesian approximation filtering method for nonlinear systems. In general, the Gaussian filters are designed for non-delayed measurementsen_US
dc.description.abstracthowever, the measurements are often delayed in practice. This paper considers that the delay is fractional multiple of sampling interval. Subsequently, it extends a significantly accurate filter, named higher degree cubature quadrature Kalman filter (HDCQKF), for handling the fractional delay problems. The simulation results conclude an improved accuracy of the HDCQKF-based delayed filtering algorithm in comparison to the popularly known cubature Kalman filter (CKF)-based delayed filtering algorithm. © 2022 IEEE.en_US
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.sourceINDICON 2022 - 2022 IEEE 19th India Council International Conferenceen_US
dc.subjectGaussian distributionen_US
dc.subjectAnd fractional delayeden_US
dc.subjectBayesianen_US
dc.subjectDelayed measurementsen_US
dc.subjectFilter-baseden_US
dc.subjectFiltering algorithmen_US
dc.subjectFiltering methoden_US
dc.subjectGaussian filteringen_US
dc.subjectGaussian filtersen_US
dc.subjectNon-linear bayesian filteringen_US
dc.subjectQuadrature Kalman filtersen_US
dc.subjectKalman filtersen_US
dc.titleHigh-degree Cubature Quadrature Kalman Filter with Fractional Delayed Measurementen_US
dc.typeConference Paperen_US
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