Extended Object Tracking Using Mixture Kalman Filtering

  • Donka Angelova
  • Lyudmila Mihaylova
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4310)


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.


Monte Carlo Size Type Data Augmentation Extended Object Dynamic Linear Model 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Berlin Heidelberg 2007

Authors and Affiliations

  • Donka Angelova
    • 1
  • Lyudmila Mihaylova
    • 2
  1. 1.Institute for Parallel Processing, Bulgarian Academy of Sciences, 25A Acad. G. Bonchev St, 1113 SofiaBulgaria
  2. 2.Department of Communication Systems, Lancaster University, South Drive, Lancaster LA1 4WAUK

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