Kernel density estimates in particle filter

The paper deals with kernel estimates of densities of filtering distributions in the particle filter. The convergence of the estimates is investigated by means of Fourier analysis. It is shown that the estimates converge to theoretical filtering densities in the mean integrated squared error under a certain assumption on the Sobolev character of the filtering densities. A sufficient condition is presented for the persistence of this Sobolev character over time.