  This letter provides an adaptive resampling method. It determines the number
of particles to resample so that the Kullback-Leibler distance (KLD) between
distribution of particles before resampling and after resampling does not
exceed a pre-specified error bound. The basis of the method is the same as
Fox's KLD-sampling but implemented differently. The KLD-sampling assumes that
samples are coming from the true posterior distribution and ignores any
mismatch between the true and the proposal distribution. In contrast, we
incorporate the KLD measure into the resampling in which the distribution of
interest is just the posterior distribution. That is to say, for sample size
adjustment, it is more theoretically rigorous and practically flexible to
measure the fit of the distribution represented by weighted particles based on
KLD during resampling than in sampling. Simulations of target tracking
demonstrate the efficiency of our method.
