Dynamic positioning particle filtering method based on the EAKF

In order to improve the positioning accuracy and reliability of ship dynamic positioning system, a method of combing Ensemble Adjustment Kalman Filter (EAKF) and Particle Filter was proposed. It's according to the use of the max of posterior probability density to generate the importance density function of particle. So that the importance probability density function could integrate into the latest observation information and accord with the posterior probability density distribution of the true state. We can use it to deal with Gaussian and nonlinear system state estimation problem effectively. The simulation results verify the effectiveness of the algorithm.