KIT | KIT-Bibliothek | Impressum | Datenschutz

Multimodal Circular Filtering Using Fourier Series

Pfaff, Florian ORCID iD icon 1; Kurz, Gerhard 1; Hanebeck, Uwe D. 1
1 Institut für Anthropomatik und Robotik (IAR), Karlsruher Institut für Technologie (KIT)

Abstract:

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.


Postprint §
DOI: 10.5445/IR/1000051023
Veröffentlicht am 15.06.2020
Scopus
Zitationen: 20
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Anthropomatik und Robotik (IAR)
Publikationstyp Proceedingsbeitrag
Publikationsjahr 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 Institute of Electrical and Electronics Engineers (IEEE)
Seiten 711-718
Schlagwörter Directional statistics, density estimation, nonlinear filtering, recursive Bayesian estimation.
Nachgewiesen in Scopus
KIT – Die Forschungsuniversität in der Helmholtz-Gemeinschaft
KITopen Landing Page