Parallel Particle Filter Toolkit

Research on using inexpensive and personal-level parallel computing architectures to speed up the implementations of the class of particle filters has been conducted. This study leverages NVIDIA Graphics Processing Units (GPUs) and multi-core CPUs (central processing units) that are quickly becoming commonly available for engineering communities. Parallelization of the unscented Kalman filter and the bootstrap particle filter, with applications in a GPS/INS (global position system/inertial navigation system) integration problem and an orbital determination problem, has been the focus of this research. It has been shown in this research that an 8-times speedup can be achieved for the unscented Kalman filter implementations with an 8-thread CPU, and up to 2 orders of magnitude speedup can be achieved using an M2090 GPU.