Improving navigational accuracy for AUVs using the MAPR Particle Filter

The objective of this paper is to compare the performance of the proposed measurement assisted partial resampling (MAPR) particle filter against the performance of the extended Kalman filter (EKF) within the context of a dynamic 6 DoF hydrodynamic system. In order to compare the respective performances of the above two filters in resolving a navigation solution, the filters are given a trajectory that closely resembles a raster scan mission, a typical mission for AUVs. This paper will show that the MAPR filter is capable of computing an estimate that, like the EKF, takes into account the dynamics of the system but like all particle filters also has the desired capability of estimating non Gaussian distributions and tracking nonlinear motion.