Scalar-weighted FastIMM Based on Fading Memory Filter Model and Adaptive Markov Transition Matrix

Basit Öğe Kaydı
dc.contributor.authorTurgut, Kubra
dc.contributor.authorHocaoglu, Ali Koksal
dc.date.accessioned2025-10-29T11:36:33Z
dc.date.issued2020
dc.departmentGebze Teknik Üniversitesi
dc.description28th Signal Processing and Communications Applications Conference (SIU) -- OCT 05-07, 2020 -- ELECTR NETWORK
dc.description.abstractIn this study, a novel target tracking algorithm based on fading memory filter model and adaptive markov transition matrix is proposed to achieve a better tracking performance for the case where the measurement noise is high, target are distant and target maneuvers are intense. The proposed adp-FastSIMM-FM algorithm has been shown to have a better position estimation than the FastIMM-FM algorithm which has a better estimation than FastIMM and FastIMM-imp. Also, adp-FastSIMM-FM algorithm has a low computational cost.
dc.description.sponsorshipIstanbul Medipol Univ
dc.identifier.isbn978-1-7281-7206-4
dc.identifier.issn2165-0608
dc.identifier.scopus2-s2.0-85100315434
dc.identifier.scopusqualityN/A
dc.identifier.urihttps://hdl.handle.net/20.500.14854/13337
dc.identifier.wosWOS:000653136100249
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isotr
dc.publisherIEEE
dc.relation.ispartof2020 28th Signal Processing and Communications Applications Conference (Siu)
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_WOS_20251020
dc.subjectTarget tracking
dc.subjectInteracting Multiple Model
dc.subjectAlpha-Beta Filter
dc.subjectAlpha-Beta-Gamma Filter
dc.titleScalar-weighted FastIMM Based on Fading Memory Filter Model and Adaptive Markov Transition Matrix
dc.typeConference Object

Dosyalar

Koleksiyon

WoS İndeksli Yayınlar Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu