Maneuvering Target Tracking with Simplified Cost Reference Particle Filters

In this paper, we investigate different variants of the recently proposed cost-reference particle filters (CRPFs) and study their application to the problem of tracking of a high-speed maneuvering target in the two-dimensional space. CRPFs drop all probabilistic assumptions required by conventional particle filters and, as a consequence, lead to practically more robust algorithms. We introduce some suitable and natural modifications of CRPFs in order to increase their efficiency and reduce their computational complexity. Computer simulations are provided to illustrate the performance of the new alternatives