Intent-informed state estimation for tracking guided targets

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dc.contributor.authorLee, Seokwon
dc.contributor.authorShin, Hyosang
dc.contributor.authorTsourdos, Antonios
dc.date.accessioned2023-11-16T11:08:34Z
dc.date.available2023-11-16T11:08:34Z
dc.date.issued2023-11-16
dc.description.abstractThis paper proposes a state estimation and prediction for tracking guided targets using intent information. A conditionally Markov process is used to describe the destination-oriented target motion, and the collision intent is incorporated through the zero-effort-miss guidance information. The expected arrival time necessary for the conditionally Markov model is determined through the collision geometry and destination motion. Finally, the Kalman filter technique is used to estimate and predict the target state. Numerical simulations demonstrate that the proposed approach can improve state estimation accuracy in both static and dynamic destination cases.en_UK
dc.identifier.citationLee S, Shin H-S, Tsourdos A. (2023) Intent-informed state estimation for tracking guided targets. Aerospace Science and Technology, Volume 143, December 2023, Article number 108713en_UK
dc.identifier.issn1270-9638
dc.identifier.urihttps://doi.org/10.1016/j.ast.2023.108713
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/20549
dc.language.isoenen_UK
dc.publisherElsevieren_UK
dc.rightsAttribution 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectState estimationen_UK
dc.subjectTrajectory predictionen_UK
dc.subjectConditionally Markov processen_UK
dc.subjectKalman filteringen_UK
dc.subjectPredictive guidanceen_UK
dc.subjectIntent inferenceen_UK
dc.titleIntent-informed state estimation for tracking guided targetsen_UK
dc.typeArticleen_UK
dcterms.dateAccepted2023-10-30

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