Gaussian implementation of the multi-Bernoulli mixture filter
Paper i proceeding, 2019

This paper presents the Gaussian implementation of the multi-Bernoulli mixture (MBM) filter. The MBM filter provides the filtering (multi-target) density for the standard dynamic and radar measurement models when the birth model is multi-Bernoulli or multi-Bernoulli mixture. Under linear/Gaussian models, the single target densities of the MBM mixture admit Gaussian closed-form expressions. Murty's algorithm is used to select the global hypotheses with highest weights. The MBM filter is compared with other algorithms in the literature via numerical simulations.

Poisson multi-Bernoulli mixtures

Multiple target tracking

multi-target conjugate priors

Författare

Angel F. Garcaa-Fernandez

University of Liverpool

Yuxuan Xia

Chalmers, Elektroteknik, Signalbehandling och medicinsk teknik, Signalbehandling

Karl Granström

Chalmers, Elektroteknik, Signalbehandling och medicinsk teknik, Signalbehandling

Lennart Svensson

Chalmers, Elektroteknik, Signalbehandling och medicinsk teknik, Signalbehandling

Jason L. Williams

Commonwealth Scientific and Industrial Research Organisation (CSIRO)

FUSION 2019 - 22nd International Conference on Information Fusion

9011346

22nd International Conference on Information Fusion, FUSION 2019
Ottawa, Canada,

Ämneskategorier

Sannolikhetsteori och statistik

Reglerteknik

Signalbehandling

Mer information

Senast uppdaterat

2020-04-08