A Comparative Study of Monte-Carlo Methods for Multitarget Tracking

Abstract : In this paper, we address the problem of tracking an unknown and time varying number of targets and their states from noisy observa- tions available at discrete intervals of time. Attention has recently fo- cused on the role of simulation-based approaches, including Monte Carlo methods, in solving multitarget tracking problem, as these methods are able to perform well for nonlinear and non-Gaussian data models. In this paper, we present a comparative study of several Monte-Carlo methods in terms of estimation quality and complexity.
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Communication dans un congrès
IEEE International Workshop on Statistical Signal Processing, Jun 2011, Nice, France. pp.205-208, 2011, 〈10.1109/SSP.2011.5967660〉
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François Septier, Julien Cornebise, Simon J. Godsill, Yves Delignon. A Comparative Study of Monte-Carlo Methods for Multitarget Tracking. IEEE International Workshop on Statistical Signal Processing, Jun 2011, Nice, France. pp.205-208, 2011, 〈10.1109/SSP.2011.5967660〉. 〈hal-00685919〉

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