Journal
IEEE TRANSACTIONS ON SIGNAL PROCESSING
Volume 62, Issue 12, Pages 3246-3260Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSP.2014.2323064
Keywords
Bayesian estimation; conjugate prior; marked point process; random finite set; target tracking
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Funding
- German Research Foundation (DFG) within the Transregional Collaborative Research Center [SFB/TRR 62]
- Australian Research Council [DE120102388, FT0991854]
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This paper proposes a generalization of the multi-Bernoulli filter called the labeled multi-Bernoulli filter that outputs target tracks. Moreover, the labeled multi-Bernoulli filter does not exhibit a cardinality bias due to a more accurate update approximation compared to the multi-Bernoulli filter by exploiting the conjugate prior form for labeled Random Finite Sets. The proposed filter can be interpreted as an efficient approximation of the delta-Generalized Labeled Multi-Bernoulli filter. It inherits the advantages of the multi-Bernoulli filter in regards to particle implementation and state estimation. It also inherits advantages of the delta-Generalized Labeled Multi-Bernoulli filter in that it outputs (labeled) target tracks and achieves better performance.
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