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Paper D. Gaussian Filtering for Polynomial Systems Based on Moment Homotopy. Edited version of the paper: M. F. Huber and U. D. Hanebeck. Gaussian Filtering for Polynomial Systems Based on Moment Homotopy. In Proceedings to the 16th International Conference on Information Fusion (Fusion), pages 1080-1087, Istanbul, Turkey, July 2013

Huber, Marco F.; Hanebeck, Uwe D.

This paper proposes Gaussian filters for polynomial systems with efficient solutions for both the prediction and the filter step. For the prediction step, computationally efficient closed-formsolutions are derived for calculating the exact moments. In order to achieve a higher estimation quality, the filter step is solved without the usual additional assumption that state and measurement are jointly Gaussian distributed. As this significantly complicates the required moment calculation, a homotopy continuation method is employed that yields almost optimal results.

Zugehörige Institution(en) am KIT Institut für Anthropomatik und Robotik (IAR)
Publikationstyp Buchaufsatz
Jahr 2015
Sprache Englisch
Identifikator URN: urn:nbn:de:swb:90-460656
KITopen-ID: 1000046065
Erschienen in Nonlinear Gaussian Filtering : Theory, Algorithms, and Applications. Ed.: M. Huber
Verlag KIT, Karlsruhe
Seiten 284-308
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