Tracking multiple spawning targets using Poisson multi-Bernoulli mixtures on sets of tree trajectories
| Autor: | García-Fernández, Ángel F., Svensson, Lennart |
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| Rok vydání: | 2021 |
| Předmět: | |
| Zdroj: | \'A. F. Garc\'ia-Fern\'andez and L. Svensson, "Tracking Multiple Spawning Targets Using Poisson Multi-Bernoulli Mixtures on Sets of Tree Trajectories," in IEEE Transactions on Signal Processing, vol. 70, pp. 1987-1999, 2022 |
| Druh dokumentu: | Working Paper |
| DOI: | 10.1109/TSP.2022.3165947 |
| Popis: | This paper proposes a Poisson multi-Bernoulli mixture (PMBM) filter on the space of sets of tree trajectories for multiple target tracking with spawning targets. A tree trajectory contains all trajectory information of a target and its descendants, which appear due to the spawning process. Each tree contains a set of branches, where each branch has trajectory information of a target or one of the descendants and its genealogy. For the standard dynamic and measurement models with multi-Bernoulli spawning, the posterior is a PMBM density, with each Bernoulli having information on a potential tree trajectory. To enable a computationally efficient implementation, we derive an approximate PMBM filter in which each Bernoulli tree trajectory has multi-Bernoulli branches, obtained by minimising the Kullback-Leibler divergence. The resulting filter improves tracking performance of state-of-the-art algorithms in a simulated scenario. Comment: Matlab code can be found at https://github.com/Agarciafernandez |
| Databáze: | arXiv |
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