Performance comparison of GPU-accelerated particle flow and particle filters

This paper presents design, implementation, and performance evaluation results of a parallel particle filter (PF) and a particle flow filter (PFF) using a Graphics Processing Unit (GPU) as a parallel computing environment to speedup the computation. Simulation results from a high dimensional nonlinear filtering problem show that, for the considered example, the parallel PFF implementation is significantly superior to the parallel PF implementation in both estimation accuracy and computational performance. It is demonstrated that using GPU can markedly accelerate both particle filters and particle flow filters through parallelization.