Show simple item record

dc.contributor.authorMahler, Ronald
dc.identifier.citationMahler, R. 2016. Integral-transform derivations of exact closed-form multitarget trackers, pp. 950-957.

© 2016 ISIF. The generalized labeled multi-Bernoulli (GLMB) filter, introduced by B.-T. Vo and B.-N. Vo in 2013, is an exact closed-form solution of the multitarget recursive Bayes filter, based on the theory of labeled random finite sets (labeled RFS's). Vo and Vo's derivation was rather long and involved. The purpose of this paper is twofold. First, to provide a more streamlined derivation of the GLMB filter using probability generating functional (p.g.fl.) methods. Second, to use p.g.fl. methods to derive another tractable, exact closed-form multitarget tracker, the labeled multi-Bernoulli mixture (LMBM) filter. This filter may be of some utility, since LMB mixtures are computationally simpler than GLMB distributions.

dc.titleIntegral-transform derivations of exact closed-form multitarget trackers
dc.typeConference Paper
dcterms.source.titleFUSION 2016 - 19th International Conference on Information Fusion, Proceedings
dcterms.source.seriesFUSION 2016 - 19th International Conference on Information Fusion, Proceedings
curtin.departmentDepartment of Electrical and Computer Engineering
curtin.accessStatusFulltext not available

Files in this item


There are no files associated with this item.

This item appears in the following Collection(s)

Show simple item record