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Sequential Monte Carlo methods for multi-target filtering with random finite sets

Abstract:

Random finite sets (RFSs) are natural representations of multi-target states and observations that allow multi-sensor multi-target filtering to fit in the unifying random set framework for data fusion. Although the foundation has been established in the form of finite set statistics (FISST), its relationship to conventional probability is not clear. Furthermore, optimal Bayesian multi-target filtering is not yet practical due to the inherent computational hurdle. Even the probability hypothes...

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Publication status:
Published

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Publisher copy:
10.1109/TAES.2005.1561884

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Institution:
University of Oxford
Department:
Oxford, MPLS, Statistics
Journal:
IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS
Volume:
41
Issue:
4
Pages:
1224-1245
Publication date:
2005-10-05
DOI:
ISSN:
0018-9251
URN:
uuid:b243946d-71f1-4497-a838-7c7289a3891c
Source identifiers:
172698
Local pid:
pubs:172698
Language:
English

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