Dynamic positioning particle filtering method based on the EnKF

In order to improve the positioning accuracy and reliability of ship dynamic positioning system and sovle the problem of Gaussian and nonlinear system state estimation effectively, a method of combing ensemble Kalman filter(EnKF) and particle filter was proposed by using the max of posterior probability density to generate the importance density function of particle to help the importance probability density function integrate into the latest observation information and at the same time more accord with the posterior probability density distribution of the true state. The effectiveness of the algorithm is verified by the simulation results.