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A Comparative Study of Monte-Carlo Methods for Multitarget Tracking

François Septier 1, 2 Julien Cornebise 3 Simon J. Godsill 4 Yves Delignon 5, 1
1 Institut TELECOM/TELECOM Lille1
2 LAGIS - Laboratoire d'Automatique, Génie Informatique et Signal
3 UBC-Computer Science - Computer Science Department
4 Signal Processing Group Dept of Engineering
5 LAGIS-SI
LAGIS - Laboratoire d'Automatique, Génie Informatique et Signal
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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CNRS | LAGIS-SI | LAGIS | IMT-LILLE-DOUAI | INSTITUT-TELECOM | IMT-NORD-EUROPE

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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, ⟨10.1109/SSP.2011.5967660⟩. ⟨hal-00685919⟩

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