Bayes filter for improving and fusing dynamic coordinate measurements

Beitrag bei einer Tagung


Details zur Publikation

Autorinnen und Autoren: Garcia E, Hausotte T
Titel Sammelwerk: 20th IMEKO World Congress 2012
Jahr der Veröffentlichung: 2012
Tagungsband: Proceedings of the XX IMEKO World Congress
Seitenbereich: CD ROM


Abstract

This paper presents a novel methodology to improve the measurement accuracy of dynamic measurements. This is achieved by deducing an online Bayes optimal estimate of the true measurand given uncertain, noisy or incomplete measurements within the framework of sequential Monte Carlo methods. The estimation problem is formulated as a general Bayesian inference problem for nonlinear dynamic systems. The optimal estimate is represented by probability density functions, which enable an online, probabilistic data fusion as well as measurement uncertainty evaluation completely conform to the "Guide to the expression of uncertainty in measurement". The efficiency and performance of the proposed methodology is verified and shown by dynamic coordinate measurements. Copyright © (2012) by the International Measurement Federation (IMEKO).


FAU-Autorinnen und Autoren / FAU-Herausgeberinnen und Herausgeber

Garcia, Elmar
Lehrstuhl für Qualitätsmanagement und Fertigungsmeßtechnik
Hausotte, Tino Prof. Dr.-Ing.
Lehrstuhl für Fertigungsmesstechnik


Zitierweisen

APA:
Garcia, E., & Hausotte, T. (2012). Bayes filter for improving and fusing dynamic coordinate measurements. In Proceedings of the XX IMEKO World Congress (pp. CD ROM). Busan, Korea.

MLA:
Garcia, Elmar, and Tino Hausotte. "Bayes filter for improving and fusing dynamic coordinate measurements." Proceedings of the XX IMEKO World Congress, Busan, Korea 2012. CD ROM.

BibTeX: 

Zuletzt aktualisiert 2019-05-06 um 14:34