Economical simulation in particle filtering using interpolation

Sampling from the importance density is often a costly aspect of particle filters. We present a method by which to replace the most computationally expensive component of the importance density with an efficient approximation, thus allowing for the propagation of a large number of particles at reduced cost. The modification is implemented within auxiliary and regularized particle filters in a numerical example based on the Kraichnan-Orszag system.