Estimation and control of multi-object systems with high-fidenlity sensor models: A labelled random finite set approach
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, informa...
| Main Author: | |
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| Format: | Thesis |
| Language: | English |
| Published: |
Curtin University
2016
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| Online Access: | http://hdl.handle.net/20.500.11937/627 |
| _version_ | 1848743433260236800 |
|---|---|
| author | Beard, Michael Anthony |
| author_facet | Beard, Michael Anthony |
| author_sort | Beard, Michael Anthony |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | 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. |
| first_indexed | 2025-11-14T05:45:29Z |
| format | Thesis |
| id | curtin-20.500.11937-627 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T05:45:29Z |
| publishDate | 2016 |
| publisher | Curtin University |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-6272017-02-20T06:40:30Z Estimation and control of multi-object systems with high-fidenlity sensor models: A labelled random finite set approach Beard, Michael Anthony 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. 2016 Thesis http://hdl.handle.net/20.500.11937/627 en Curtin University fulltext |
| spellingShingle | Beard, Michael Anthony Estimation and control of multi-object systems with high-fidenlity sensor models: A labelled random finite set approach |
| title | Estimation and control of multi-object systems with high-fidenlity sensor models: A labelled random finite set approach |
| title_full | Estimation and control of multi-object systems with high-fidenlity sensor models: A labelled random finite set approach |
| title_fullStr | Estimation and control of multi-object systems with high-fidenlity sensor models: A labelled random finite set approach |
| title_full_unstemmed | Estimation and control of multi-object systems with high-fidenlity sensor models: A labelled random finite set approach |
| title_short | Estimation and control of multi-object systems with high-fidenlity sensor models: A labelled random finite set approach |
| title_sort | estimation and control of multi-object systems with high-fidenlity sensor models: a labelled random finite set approach |
| url | http://hdl.handle.net/20.500.11937/627 |