Trajectory multi-Bernoulli filters for multi-target tracking based on sets of trajectories
Paper i proceeding, 2020

This paper presents two multi-Bernoulli filters on sets of trajectories for multiple target tracking. The first filter provides a multi-Bernoulli approximation of the posterior density over the set of alive trajectories at the current time step. The second filter provides a multi-Bernoulli approximation of the posterior density over the set of all trajectories (alive and dead) up to the current time. We also explain the Gaussian implementation of the filters and compare them with other multiple target tracking algorithms in a simulated scenario.

sets of trajectories.

multi-target conjugate priors

Multiple target tracking

Poisson multi-Bernoulli mixtures

Författare

Angel Garcia

University of Liverpool

Lennart Svensson

Chalmers, Elektroteknik, Signalbehandling och medicinsk teknik, Signalbehandling

Jason L. Williams

Commonwealth Scientific and Industrial Research Organisation (CSIRO)

Yuxuan Xia

Chalmers, Elektroteknik, Signalbehandling och medicinsk teknik, Signalbehandling

Karl Granström

Chalmers, Elektroteknik, Signalbehandling och medicinsk teknik, Signalbehandling

2020 IEEE 23rd International Conference on Information Fusion (FUSION)

313-320 9190554

2020 IEEE 23rd International Conference on Information Fusion (FUSION)
Rustenburg, South Africa,

Målföljning och djup maskininlärning för trajektorieskattning med tillämpning mot noggranna referenssystem

VINNOVA (2017-05521), 2018-07-01 -- 2022-06-30.

Styrkeområden

Informations- och kommunikationsteknik

Transport

Ämneskategorier

Reglerteknik

Signalbehandling

Datavetenskap (datalogi)

DOI

10.23919/FUSION45008.2020.9190554

Mer information

Senast uppdaterat

2021-07-27