Improved particle filters for ballistic target tracking

We present in this paper two improved particle filter algorithms for ballistic target tracking. The first algorithm is a sampling/importance resampling (SIR) filter that uses an optimized importance function plus residual resampling to combat particle degeneracy, and also incorporates a Metropolis-Hastings (MH) move step to reduce particle impoverishment. The second proposed algorithm is an auxiliary particle filter (APF). Both algorithms show good performance results when compared to the ideal posterior Cramer-Rao lower bound for the mean square estimation error.