Joint Detection and Tracking of Occluded Target Using Lidar

dc.contributor.authorKorkut, Musa Gokhan
dc.contributor.authorAltun, Muhammet
dc.contributor.authorGullu, Ali Ihsan
dc.contributor.authorGunes, Ahmet
dc.date.accessioned2025-10-29T11:15:26Z
dc.date.issued2023
dc.departmentGebze Teknik Üniversitesi
dc.description31st IEEE Conference on Signal Processing and Communications Applications (SIU) -- JUL 05-08, 2023 -- Istanbul Tech Univ, Ayazaga Campus, Istanbul, TURKEY
dc.description.abstractTarget tracking in transportation vehicles is important from both civilian and military perspectives. Objects that obstruct the sensor's field of view create occlusion regions in target tracking. The literature has developed dynamic solutions to address the problems arising from the target entering the sensor's occlusion spot behind an obstacle and detecting occlusion regions. In this study, target tracking using lidar is performed with a stationary vehicle obstacle and a moving vehicle in the Gazebo simulation environment. A solution is proposed for velocity disturbances during entry into the occlusion region in this environment. After comparing the performance of target tracking filters in the simulation environment, the algorithms are tested in a real-world scenario where a similar simulation environment is set up. Two different Bernoulli filters are implemented based on the nearest neighbor and probabilistic data association mechanisms. The results are evaluated using the Optimal Sub-Pattern Assignment metrics.
dc.description.sponsorshipIEEE,TUBITAK BILGEM,Turkcell
dc.identifier.doi10.1109/SIU59756.2023.10223946
dc.identifier.isbn979-8-3503-4355-7
dc.identifier.issn2165-0608
dc.identifier.scopus2-s2.0-85173531838
dc.identifier.scopusqualityN/A
dc.identifier.urihttps://doi.org/10.1109/SIU59756.2023.10223946
dc.identifier.urihttps://hdl.handle.net/20.500.14854/7092
dc.identifier.wosWOS:001062571000173
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isotr
dc.publisherIEEE
dc.relation.ispartof2023 31st 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.subjectOcclusion
dc.subjectlidar
dc.subjecttarget tracking
dc.subjectprobabilistic data association
dc.subjectnearest neighbor
dc.titleJoint Detection and Tracking of Occluded Target Using Lidar
dc.typeConference Object

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