Show simple item record

dc.contributor.authorBeard, Michael Anthony
dc.contributor.supervisorDr Sanjeev Arulampalam
dc.contributor.supervisorProf. Ba-Ngu Vo
dc.contributor.supervisorDr Ba Tuong Vo

Principled and novel multi-object tracking algorithms are proposed, that have the ability to optimally process realistic sensor data, by accommodating complex observational phenomena such as merged measurements and extended targets. Additionally, a sensor control scheme based on a tractable, information theoretic objective is proposed, the goal of which is to optimise tracking performance in multi-object scenarios. The concept of labelled random finite sets is adopted in the development of these new techniques.

dc.publisherCurtin University
dc.titleEstimation and control of multi-object systems with high-fidenlity sensor models: A labelled random finite set approach
curtin.departmentDepartment of Electrical and Computer Engineering
curtin.accessStatusOpen access

Files in this item


This item appears in the following Collection(s)

Show simple item record