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dc.contributor.authorDo, Cong-Thanh
dc.contributor.supervisorBa-Ngu Voen_US
dc.contributor.supervisorBa Tuong Voen_US

This dissertation presents novel multi-target tracking algorithms that obviate the need for prior knowledge of system parameters such as clutter rate, detection probabilities, and birth models. Information on these parameters is unknown but important to tracking performance. The proposed algorithms exploit the advantages of existing RFS trackers and filters by bootstrapping them. This configuration inherits the efficiency of tracking target trajectories from the RFS trackers and low complexity in parameter estimation from the RFS filters.

dc.publisherCurtin Universityen_US
dc.titleRobust Multi-target Tracking with Bootstrapped-GLMB Filteren_US
curtin.departmentSchool of Electrical Engineering, Computing and Mathematical Sciencesen_US
curtin.accessStatusOpen accessen_US
curtin.facultyScience and Engineeringen_US
curtin.contributor.orcidDo, Cong-Thanh [0000-0003-1748-2846]en_US

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