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Poisson Multi-Bernoulli Mixture Filter: Direct Derivation and Implementation

Open access
Garcia-Fernandez, Angel F., Williams, Jason L., Granstrom, Karl, Svensson, Lennart·2018·IEEE Transactions on Aerospace and Electronic Systems

Abstract

We provide a derivation of the Poisson multi-Bernoulli mixture (PMBM) filter for multitarget tracking with the standard point target measurements without using probability generating functionals or functional derivatives. We also establish the connection with the δ-generalized labeled multi-Bernoulli (δ-GLMB) filter, showing that a δ-GLMB density represents a multi-Bernoulli mixture with labeled targets soit can be seen as a special case of PMBM. In addition, we propose an implementation for linear/Gaussian dynamic and measurement models and how to efficiently obtain typical estimators in the literature from the PMBM. The PMBM filter is shown to outperform other filters in the literature in a challenging scenario.

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Metadata

Authors
Garcia-Fernandez, A. F., Williams, J. L., Granstrom, K., & Svensson, L.
Venue
IEEE Transactions on Aerospace and Electronic Systems
Published
2018-08
Volume
54
Issue
4
Pages
1883-1901
ISSN
  • 0018-9251 (ISSN-L)
  • 1557-9603
  • 2371-9877
OpenAlex
W2595600061
Cited by
284
References
36
FWCI
12.16
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Poisson Multi-Bernoulli Mixture Filter: Direct Derivation and Implementation. https://app.cochat.ai/papers/10.1109/taes.2018.2805153
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Garcia-Fernandez, A. F., Williams, J. L., Granstrom, K., & Svensson, L. (2018). Poisson Multi-Bernoulli Mixture Filter: Direct Derivation and Implementation. IEEE Transactions on Aerospace and Electronic Systems. https://doi.org/10.1109/taes.2018.2805153

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