Robust Multi-Bernoulli Filtering
| dc.contributor.author | Vo, Ba Tuong | |
| dc.contributor.author | Vo, Ba-Ngu | |
| dc.contributor.author | Hoseinnezhad, R. | |
| dc.contributor.author | Mahler, R. | |
| dc.date.accessioned | 2017-01-30T15:28:54Z | |
| dc.date.available | 2017-01-30T15:28:54Z | |
| dc.date.created | 2014-03-12T20:01:03Z | |
| dc.date.issued | 2013 | |
| dc.identifier.citation | Vo, Ba-Tuong and Vo, Ba-Ngu and Hoseinnezhad, Reza and Mahler, Ronald P.S. 2013. Robust Multi-Bernoulli Filtering. IEEE Journal of Selected Topics in Signal Processing. 7 (3): pp. 399-409. | |
| dc.identifier.uri | http://hdl.handle.net/20.500.11937/46736 | |
| dc.identifier.doi | 10.1109/JSTSP.2013.2252325 | |
| dc.description.abstract |
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. | |
| dc.publisher | Institute of Electrical and Electronics Engineers | |
| dc.title | Robust Multi-Bernoulli Filtering | |
| dc.type | Journal Article | |
| dcterms.source.volume | 7 | |
| dcterms.source.number | 3 | |
| dcterms.source.startPage | 399 | |
| dcterms.source.endPage | 409 | |
| dcterms.source.issn | 1932-4553 | |
| dcterms.source.title | IEEE Journal on Selected Topics in Signal Processing | |
| curtin.department | ||
| curtin.accessStatus | Fulltext not available |