Garcia-Fernandez, Angel F 
ORCID: 0000-0002-6471-8455, Xia, Yuxuan and Svensson, Lennart
(2023)
Poisson Multi-Bernoulli Mixture Filter With General Target-Generated Measurements and Arbitrary Clutter.
IEEE TRANSACTIONS ON SIGNAL PROCESSING, 71.
pp. 1895-1906.
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Abstract
This article shows that the Poisson multi-Bernoulli mixture (PMBM) density is a multi-target conjugate prior for general target-generated measurement distributions and arbitrary clutter distributions. That is, for this multi-target measurement model and the standard multi-target dynamic model with Poisson birth model, the predicted and filtering densities are PMBMs. We derive the corresponding PMBM filtering recursion. Based on this result, we implement a PMBM filter for point-target measurement models and negative binomial clutter density in which data association hypotheses with high weights are chosen via Gibbs sampling. We also implement an extended target PMBM filter with clutter that is the union of Poisson-distributed clutter and a finite number of independent clutter sources. Simulation results show the benefits of the proposed filters to deal with non-standard clutter.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | Clutter, Density measurement, Standards, Predictive models, Probabilistic logic, Data models, Sea measurements, Multi-target filtering, Poisson multi-Bernoulli mixtures, Gibbs sampling, arbitrary clutter |
| Divisions: | Faculty of Science and Engineering > School of Electrical Engineering, Electronics and Computer Science |
| Depositing User: | Symplectic Admin |
| Date Deposited: | 02 Jun 2023 07:47 |
| Last Modified: | 16 Mar 2024 02:45 |
| DOI: | 10.1109/TSP.2023.3278944 |
| Related URLs: | |
| URI: | https://livrepository.liverpool.ac.uk/id/eprint/3170788 |
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