Estimation with Applications to Tracking and Navigation
Estimation with Applications to Tracking and Navigation
Estimation of Markovian Jump Systems with Unknown Transition Probabilities through Bayesian Sampling
NMA '02 Revised Papers from the 5th International Conference on Numerical Methods and Applications
Multilevel mixture Kalman filter
EURASIP Journal on Applied Signal Processing
Monte Carlo Strategies in Scientific Computing
Monte Carlo Strategies in Scientific Computing
A monte carlo algorithm for state and parameter estimation of extended targets
ICCS'06 Proceedings of the 6th international conference on Computational Science - Volume Part III
Adaptive joint detection and decoding in flat-fading channels via mixture Kalman filtering
IEEE Transactions on Information Theory
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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.