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URN: urn:nbn:de:swb:90-351321

Progressive Correction for Deterministic Dirac Mixture Approximations

Ruoff, Patrick; Krauthausen, Peter; Hanebeck, Uwe D.

Since the advent of Monte-Carlo particle filtering, particle representations of densities have become increasingly popular due to their flexibility and implicit adaptive resolution. In this paper, an algorithm for the multiplication of a systematic Dirac mixture (DM) approximation with a continuous likelihood function is presented, which applies a progressive correction scheme, in order to avoid the particle degeneration problem. The preservation of sample regularity and therefore, representation quality of the underlying smooth density, is ensured by including a new measure of smoothness for Dirac mixtures, the DM energy, into the distance measure. A comparison to common correction schemes in Monte-Carlo methods reveals large improvements especially in cases of small overlap between the likelihood and prior density, as well as for multi-modal likelihoods.

Zugehörige Institution(en) am KIT Institut für Anthropomatik (IFA)
Publikationstyp Proceedingsbeitrag
Jahr 2011
Sprache Englisch
Identifikator ISBN: 978-1-4577-0267-9
KITopen ID: 1000035132
Erschienen in Proceedings of the 14th International Conference on Information Fusion (Fusion 2011), Chicago, Illinois, USA, 5-8 July 2011
Verlag IEEE, Piscataway
Seiten 8
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