Backward simulation for sets of trajectories
Paper i proceeding, 2020

This paper presents a solution for recovering full trajectory information, via the calculation of the posterior of the set of trajectories, from a sequence of multitarget (unlabelled) filtering densities and the multitarget dynamic model. Importantly, the proposed solution opens an avenue of trajectory estimation possibilities for multitarget filters that do not explicitly estimate trajectories. In this paper, we first derive a general multitrajectory forward-backward smoothing equation based on sets of trajectories and the random finite set framework. Then we show how to sample sets of trajectories using backward simulation when the multitarget filtering densities are multi-Bernoulli processes. The proposed approach is demonstrated in a simulation study.

sets of trajectories

Multitarget smoothing

backward simulation

forward-backward smoothing

Författare

Yuxuan Xia

Chalmers, Elektroteknik, Signalbehandling och medicinsk teknik, Signalbehandling

Lennart Svensson

Chalmers, Elektroteknik, Signalbehandling och medicinsk teknik, Signalbehandling

Angel Garcia

University of Liverpool

Karl Granström

Chalmers, Elektroteknik, Signalbehandling och medicinsk teknik, Signalbehandling

Jason L. Williams

Commonwealth Scientific and Industrial Research Organisation (CSIRO)

Proceedings of 2020 23rd International Conference on Information Fusion, FUSION 2020

9190164

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

Målföljning och djup maskininlärning för trajektorieskattning med tillämpning mot noggranna referenssystem

VINNOVA, 2018-07-01 -- 2022-06-30.

Ämneskategorier

Beräkningsmatematik

Sannolikhetsteori och statistik

Signalbehandling

DOI

10.23919/FUSION45008.2020.9190164

Mer information

Senast uppdaterat

2020-12-23