The multitarget Set JPDA filter with target identity
Conference contribution, 2011

The Set JPDA (SJPDA) filter is a recently developed multi-target tracking filter that utilizes the relation between the density of a random finite set and the ordinary density of a state vector to improve on the Joint Probabilistic Data Association (JPDA) filter. One advantage to the filter is the improved accuracy of the Gaussian approximations of the JPDA, which result in avoidance of track coalescence. In the original presentation of the SJPDA filter, the focus was on problems where target identity is not relevant, and it was shown that the filter performs better than the JPDA filter for such problems. The improved performance of the SJPDA is due to its relaxation of the labeling constraint that hampers most tracking approaches. However, if track identity is of interest a record of it may be kept even with a label-free approach such as the SJPDA: label-free targets are localized via the SJPDA, and then the identities are recalled as an overlay.

JPDA

SJPDA

estimation

target identity

Target tracking

finite set statistics

Author

Daniel Svensson

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

Lennart Svensson

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

Marco Guerriero

David Crouse

P. Willett

Proceedings of SPIE: Signal Processing, Sensor Fusion, and Target Recognition XX. Conference on Signal Processing, Sensor Fusion, and Target Recognition XX Orlando, FL, APR 25-27, 2011

0277-786X (ISSN)

Vol. 8050

Areas of Advance

Information and Communication Technology

Transport

Subject Categories

Probability Theory and Statistics

Signal Processing

Other Electrical Engineering, Electronic Engineering, Information Engineering

DOI

10.1117/12.886946

ISBN

978-0-81948-624-0

More information

Created

10/8/2017