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 978-3-540-70940-4Full text not available from this repository.
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|
|Deposited By:||Dr L Mihaylov|
|Deposited On:||28 Jan 2008 08:55|
|Last Modified:||23 Mar 2017 01:16|
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