Abstract
Particle filters have been proven to be very effective for nonlinear/non-Gaussian filtering. However, the most notorious disadvantage of a particle filter is its formidable computational complexity, since hundreds (even thousands) of particles are usually needed to achieve a required approximation accuracy. It has also been proven that one of the techniques of truly solving a computational problem is multiresolutional processing, both in temporal and spatial domains. Therefore, in this paper we propose a multiresolutional particle filter in the spatial domain using thresholded wavelets to reduce significantly the number of particles, meanwhile maintaining the full strength of a particle filter.
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