Particle filter based MAP state estimation: a comparison

Saha, S. and Boers, Y. and Driessen, J.N. and Mandal, P.K. and Bagchi, A. (2009) Particle filter based MAP state estimation: a comparison. In: 12th International Conference on Information Fusion 2009, 6-9 July, 2009, Seattle, USA.

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Abstract:	MAP estimation is a good alternative to MMSE for certain applications involving nonlinear non Gaussian systems. Recently a new particle filter based MAP estimator has been derived. This new method extracts the MAP directly from the output of a running particle filter. In the recent past, a Viterbi algorithm based MAP sequence estimator has been developed. In this paper, we compare these two methods for estimating the current state and the numerical results show that the former performs better.
Item Type:	Conference or Workshop Item
Faculty:	Electrical Engineering, Mathematics and Computer Science (EEMCS)
Research Group:	Stochastic Systems and Signals (SST)
Link to this item:	http://purl.utwente.nl/publications/68153
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