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Multimodal Circular Filtering Using Fourier Series

Florian Pfaff; Gerhard Kurz; Uwe D. Hanebeck

Recursive filtering with multimodal likelihoods and transition
densities on periodic manifolds is, despite the compact domain, still an
open problem. We propose a novel filter for the circular case that performs
well compared to other state-of-the-art filters adopted from linear
domains. The filter uses a limited number of Fourier coefficients of the
square root of the density. This representation is preserved throughout
filter and prediction steps and allows obtaining a valid density at any
point in time. Additionally, analytic formulae for calculating Fourier
coefficients of the square root of some common circular densities are
provided. In our evaluation, we show that this new filter performs well in
both unimodal and multimodal scenarios while requiring only a reasonable
number of coefficients.

Zugehörige Institution(en) am KIT Institut für Anthropomatik und Robotik (IAR)
Publikationstyp Proceedingsbeitrag
Jahr 2015
Sprache Englisch
Identifikator ISBN: 978-0-9824-4386-6
KITopen-ID: 1000051023
Erschienen in Proceedings of the 18th International Conference on Information Fusion (Fusion 2015), 6-9 July 2015, Washington, DC, USA
Verlag IEEE, Piscataway (NJ)
Seiten 711-718
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