Particle PHD forward filter-backward simulator for targets in close proximity
Paper i proceeding, 2013

In this work, we introduce the particle PHD forward filter - backward simulator (PHD-FFBSi) capable of dealing with uncertainties in the labeling of tracks that appear when tracking two targets in close proximity with measurements that do not discriminate between them. The Forward Filter Backward Simulator is a smoothing technique based on rejection sampling for the calculation of the probabilities of association between targets and tracks. The forward filter is a particle implementation of the Probability Hypothesis Density (PHD) filter that presents advantages over an SIR filter. Difficulties that arise due to the presence of target birth and death processes are addressed through modifications to the fast FFBSi. Simulations show the new particle filter of asymptotically linear complexity in the number of particles calculates correct target label probabilities at varying levels of measurement noise.

smoothing

closely spaced targets

FFBSi

PHD

particle filter

Författare

R. Georgescu

University of Connecticut

Peter Willett

University of Connecticut

Lennart Svensson

Chalmers, Signaler och system, Signalbehandling och medicinsk teknik, Signalbehandling

ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

1520-6149 (ISSN)

6387-6391

Ämneskategorier

Signalbehandling

DOI

10.1109/ICASSP.2013.6638895

ISBN

978-147990356-6