Extended Target Tracking with a Cardinalized Probability Hypothesis Density Filter
2011 (English)Report (Other academic)
This paper presents a cardinalized probability hypothesis density (CPHD) filter for extended targets that can result in multiple measurements at each scan. The probability hypothesis density (PHD) filter for such targets has already been derived by Mahler and a Gaussian mixture implementation has been proposed recently. This work relaxes the Poisson assumptions of the extended target PHD filter in target and measurement numbers to achieve better estimation performance. A Gaussian mixture implementation is described. The early results using real data from a laser sensor confirm that the sensitivity of the number of targets in the extended target PHD filter can be avoided with the added flexibility of the extended target CPHD filter.
Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2011. , 16 p.
LiTH-ISY-R, ISSN 1400-3902 ; 2999
Multiple target tracking, extended targets, random sets, probability hypothesis density, cardinalized, PHD, CPHD, Gaussian mixture, laser
IdentifiersURN: urn:nbn:se:liu:diva-97943ISRN: LiTH-ISY-R-2999OAI: oai:DiVA.org:liu-97943DiVA: diva2:650738