Gamma Gaussian inverse-Wishart Poisson multi-Bernoulli filter for extended target tracking
Paper i proceeding, 2016

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.

Poisson distributed number

gamma Gaussian inverse-Wishart Poisson multi-Bernoulli filter

GGIW-PMBM filter

target tracking

gamma-Gaussian-inverse Wishart

Författare

Karl Granström

Signaler och system, Signalbehandling och medicinsk teknik, Signalbehandling

Maryam Fatemi

Signaler och system, Signalbehandling och medicinsk teknik, Signalbehandling

Lennart Svensson

Signaler och system, Signalbehandling och medicinsk teknik, Signalbehandling

FUSION 2016 - 19th International Conference on Information Fusion, Proceedings

893-900

Styrkeområden

Informations- och kommunikationsteknik

Transport

Ämneskategorier

Signalbehandling

ISBN

978-0-9964-5274-8