Extended Target Tracking with a Cardinalized Probability Hypothesis Density Filter
2011 (English)In: Proceedings of 2011 International Conference on Information Fusion (FUSION), 2011Conference paper (Refereed)
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
CPHD filter, Gaussian mixture, Multiple target tracking, PHD, cardinalized, extended targets, laser, probability hypothesis density, random sets
National CategoryControl Engineering
IdentifiersURN: urn:nbn:se:liu:diva-82013OAI: oai:DiVA.org:liu-82013DiVA: diva2:557436
14th International Conference on Information Fusion