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Extended Object Tracking Using Mixture Kalman Filtering.

Angelova, D and Mihaylova, L (2007) Extended Object Tracking Using Mixture Kalman Filtering. In: Lecture Notes in Computer Science. Springer-Verlag,, Heidelberg, pp. 122-130. ISBN 978-3-540-70940-4

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Abstract

This paper addresses the problem of tracking extended objects. Examples of extended objects are ships and a convoy of vehicles. Such kind of objects have particularities which pose challenges in front of methods considering the extended object as a single point. Measurements of the object extent can be used for estimating size parameters of the object, whose shape is modeled by an ellipse. This paper proposes a solution to the extended object tracking problem by mixture Kalman filtering. The system model is formulated in a conditional dynamic linear (CDL) form. Based on the specifics of the task, two latent indicator variables are proposed, characterising the mode of maneuvering and size type, respectively. The developed Mixture Kalman filter is validated and evaluated by computer simulation.

Item Type: Contribution in Book/Report/Proceedings
Uncontrolled Keywords: nonlinear estimation ; Monte Cralo methods ; parameter estimation ; stochastic filters ; extended objects ; DCS-publications-id ; incoll-66 ; DCS-publications-credits ; dsp ; DCS-publications-personnel-id ; 121
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Departments: Faculty of Science and Technology > School of Computing & Communications
ID Code: 1013
Deposited By: Dr L Mihaylov
Deposited On: 28 Jan 2008 08:55
Refereed?: No
Published?: Published
Last Modified: 17 Sep 2013 09:16
Identification Number:
URI: http://eprints.lancs.ac.uk/id/eprint/1013

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