Trajectory Estimation of Autonomous Surface Vehicle using Square Root Ensemble Kalman Filter

Indonesia is an archipelago and maritime country. Thus, Indonesia has the potential to develop marine tourism. In order to attract tourists to enjoy the sea view, it is necessary to provide a safe transportation with a small risk. One of the vehicles that can be used to support the marine tourism is an unmanned ship or Autonomous Surface Vehicle (ASV). ASV can move without any crew and it can be controlled from distance. This study uses a Touristant ASV with a length of 4.12 meters, a diameter of 1.625 m and a height of 1.027 meters. The contribution of this paper is the estimation of a Touristant ASV trajectory via its nonlinear model under some noises by using Square Root Ensemble Kalman Filter (EnSRKF) method. The noises are wind velocity and sea wave. We have conducted simulations by using 400 and 500 ensembles. The results show that the error in x position is 0.02 meters, a y position is 0.031 meters, and an xy position is 0.015 meter, with an accuracy of above 96%. In the simulation, we use x and y position because the vehicle is always in the surface.