Estimation and control of multi-object systems with high-fidenlity sensor models: A labelled random finite set approach
Beard, Michael Anthony
Dr Sanjeev Arulampalam
Prof. Ba-Ngu Vo
Dr Ba Tuong Vo
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Department of Electrical and Computer Engineering
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.
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