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Gamma Gaussian inverse-Wishart Poisson multi-Bernoulli filter for extended target tracking

Karl Granström (Institutionen för signaler och system, Signalbehandling) ; Maryam Fatemi (Institutionen för signaler och system, Signalbehandling) ; Lennart Svensson (Institutionen för signaler och system, Signalbehandling)
FUSION 2016 - 19th International Conference on Information Fusion, Proceedings p. 893-900. (2016)
[Konferensbidrag, refereegranskat]

This paper presents a gamma-Gaussian-inverse Wishart (GGIW) implementation of a Poisson multi-Bernoulli mixture (PMBM) filter for multiple extended target tracking. The GGIW density is the single extended target conjugate prior assuming a Poisson distributed number of Gaussian distributed measurements, and the PMBM density is the multi-object conju- gate prior assuming Poisson target measurements, Poisson clutter, and Poisson target birth. Specifically, the Poisson part of the GGIW-PMBM multi-object density represents the distribution of targets that have not yet been detected, and the multi-Bernoulli mixture part of the GGIW-PMBM multi-object density represents the distribution of targets that have been detected at least once. The update and the prediction of the GGIW-PMBM density parameters are given, and the filter is evaluated in a simulation study. The results show that the GGIW-PMBM filter outperforms PHD and CPHD filters for extended target tracking.

Nyckelord: GGIW-PMBM filter, gamma Gaussian inverse-Wishart Poisson multi-Bernoulli filter, target tracking, gamma-Gaussian-inverse Wishart, Poisson distributed number



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Denna post skapades 2016-11-14. Senast ändrad 2017-01-11.
CPL Pubid: 245112

 

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