The Labeled Multi-Bernoulli Filter

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 filte...

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Bibliographic Details
Published in:IEEE transactions on signal processing 2014-06, Vol.62 (12), p.3246-3260
Main Authors: Reuter, Stephan, Vo, Ba-Tuong, Vo, Ba-Ngu, Dietmayer, Klaus
Format: Article
Language:English
Subjects:
Applied sciences
Approximation methods
Bayesian estimation
Clutter
conjugate prior
Current measurement
Detection, estimation, filtering, equalization, prediction
Exact sciences and technology
Information, signal and communications theory
marked point process
Materials
Radar tracking
random finite set
Signal and communications theory
Signal, noise
Target tracking
Telecommunications and information theory
Vectors
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Summary: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.
ISSN:1053-587X
1941-0476
DOI:10.1109/TSP.2014.2323064