Set JPDA algorithm for tracking unordered sets of targets
Paper in proceedings, 2009

In this article we show that traditional tracking algorithms should be adjusted when the objective is to recursively estimate an unordered (unlabeled) set of target state vectors, i.e., when it is not of importance to try to preserve target identities over time. We study scenarios where the number of targets is known, and propose a new version of the joint probabilistic data association (JPDA) filter that we call set JPDA (SJPDA). Simulations show that the new filter outperforms the JPDA in a two-target scenario when evaluated according to the mean optimal subpattern assignment (MOSPA) measure.

JPDA

Tracking

target identity

OSPA

Random finite sets

SJPDA

Author

Lennart Svensson

Chalmers, Signals and Systems, Signalbehandling och medicinsk teknik, Signal Processing

Daniel Svensson

Chalmers, Signals and Systems, Signalbehandling och medicinsk teknik, Signal Processing

P. Willett

Proceedings of the 12th International Conference on Information Fusion

1187-1194

Subject Categories

Signal Processing

Other Electrical Engineering, Electronic Engineering, Information Engineering

ISBN

978-0-9824-4380-4

More information

Created

10/7/2017