  Particle filters are applicable to a wide range of nonlinear, non-Gaussian
state-space models and have already been applied to a variety of problems.
However, there is a problem in the calculation of smoothed distributions, where
particles gradually degenerate and accuracy is reduced. The purpose of this
paper is to consider the possibility of generating multiple particles in the
prediction step of the particle filter and to empirically verify the effect
using real data.
