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On using likelihood-adjusted proposals in particle filtering: local importance sampling

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2 Author(s)
Torma, P. ; Eotvos Lorand Univ., Budapest, Hungary ; Szepesvari, C.

An unsatisfactory property of particle filters is that they may become inefficient when the observation noise is low. In this paper we consider a simple-to-implement particle filter, called 'LIS-based particle filter', whose aim is to overcome the above mentioned weakness. LIS-based particle filters sample the particles in a two-stage process that uses information of the most recent observation, too. Experiments with the standard bearings-only tracking problem indicate that the proposed new particle filter method is indeed a viable alternative to other methods.

Published in:

Image and Signal Processing and Analysis, 2005. ISPA 2005. Proceedings of the 4th International Symposium on

Date of Conference:

15-17 Sept. 2005