Robust Multi-Bernoulli Filtering
In Bayesian multi-target filtering knowledge of parameters such as clutter intensity and detection probability profile are of critical importance. Significant mismatches in clutter and detection model parameters results in biased estimates. In this paper we propose a multi-target filtering solution...
| Main Authors: | , , , |
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| Format: | Journal Article |
| Published: |
Institute of Electrical and Electronics Engineers
2013
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| Online Access: | http://hdl.handle.net/20.500.11937/46736 |
| _version_ | 1848757643219304448 |
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| author | Vo, Ba Tuong Vo, Ba-Ngu Hoseinnezhad, R. Mahler, R. |
| author_facet | Vo, Ba Tuong Vo, Ba-Ngu Hoseinnezhad, R. Mahler, R. |
| author_sort | Vo, Ba Tuong |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | In Bayesian multi-target filtering knowledge of parameters such as clutter intensity and detection probability profile are of critical importance. Significant mismatches in clutter and detection model parameters results in biased estimates. In this paper we propose a multi-target filtering solution that can accommodate non-linear target models and an unknown non-homogeneous clutter and detection profile. Our solution is based on the multi-target multi-Bernoulli filter that adaptively learns non-homogeneous clutter intensity and detection probability while filtering. |
| first_indexed | 2025-11-14T09:31:21Z |
| format | Journal Article |
| id | curtin-20.500.11937-46736 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T09:31:21Z |
| publishDate | 2013 |
| publisher | Institute of Electrical and Electronics Engineers |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-467362017-09-13T14:08:48Z Robust Multi-Bernoulli Filtering Vo, Ba Tuong Vo, Ba-Ngu Hoseinnezhad, R. Mahler, R. In Bayesian multi-target filtering knowledge of parameters such as clutter intensity and detection probability profile are of critical importance. Significant mismatches in clutter and detection model parameters results in biased estimates. In this paper we propose a multi-target filtering solution that can accommodate non-linear target models and an unknown non-homogeneous clutter and detection profile. Our solution is based on the multi-target multi-Bernoulli filter that adaptively learns non-homogeneous clutter intensity and detection probability while filtering. 2013 Journal Article http://hdl.handle.net/20.500.11937/46736 10.1109/JSTSP.2013.2252325 Institute of Electrical and Electronics Engineers restricted |
| spellingShingle | Vo, Ba Tuong Vo, Ba-Ngu Hoseinnezhad, R. Mahler, R. Robust Multi-Bernoulli Filtering |
| title | Robust Multi-Bernoulli Filtering |
| title_full | Robust Multi-Bernoulli Filtering |
| title_fullStr | Robust Multi-Bernoulli Filtering |
| title_full_unstemmed | Robust Multi-Bernoulli Filtering |
| title_short | Robust Multi-Bernoulli Filtering |
| title_sort | robust multi-bernoulli filtering |
| url | http://hdl.handle.net/20.500.11937/46736 |