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Extended Object and Group Tracking with Elliptic Random Hypersurface Models

Baum, Marcus; Noack, Benjamin; Hanebeck, Uwe D.


This paper provides new results and insights for tracking an extended target object modeled with an Elliptic Random Hypersurface Model (RHM). An Elliptic RHM specifies the relative squared Mahalanobis distance of a measurement source to the center of the target object by means of a one-dimensional random scaling factor. It is shown that uniformly distributed measurement sources on an ellipse lead to a uniformly distributed squared scaling factor. Furthermore, a Bayesian inference mechanisms tailored to elliptic shapes is introduced, which is also suitable for scenarios with high measurement noise. Closed-form expressions for the measurement update in case of Gaussian and uniformly distributed squared scaling factors are derived.

Volltext §
DOI: 10.5445/IR/1000035087
DOI: 10.1109/icif.2010.5711854
Zitationen: 79
Cover der Publikation
Zugehörige Institution(en) am KIT Fakultät für Informatik – Institut für Anthropomatik (IFA)
Publikationstyp Proceedingsbeitrag
Publikationsjahr 2010
Sprache Englisch
Identifikator ISBN: 978-0-9824438-1-1
KITopen-ID: 1000035087
Erschienen in Proceedings of the 13th International Conference on Information Fusion (Fusion 2010), Edinburgh, United Kingdom, 26-29 July 2010
Verlag Institute of Electrical and Electronics Engineers (IEEE)
Seiten 8 S.
Nachgewiesen in Dimensions
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