Extended Target Tracking with a Cardinalized Probability Hypothesis Density Filter, Report no. LiTH-ISY-R-2999

This technical report presents a cardinalized probability hypothesis density (CPHD) lter for extended targets that can result in multiple measurements at each scan. The probability hypothesis density (PHD) lter 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 lter 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 con rm that the sensitivity of the number of targets in the extended target PHD lter can be avoided with the added exibility of the extended target CPHD lter.