Estimation of UNUSAITS AUV Position of Motion Using Extended Kalman Filter (EKF)

Abstract

One of the underwater robots is an Autonomous Underwater Vehicle (AUV). AUV is relatively flexible for ocean observation because it does not need cables and can swim freely without obstacles. This paper presents the results of the development of the AUV navigation and.guidance system through the estimated trajectory. The AUV motion system has 6 degrees of freedom (DOF). The nonlinear.model of six degrees of freedom, applied to AUV, was linearized using Jacobian.matrix. The resulted linear system was then implemented as a platform to estimate the trajectory. One of the trajectory estimation methods is the Extended Kalman.Filter (EKF) method. This paper implements the EKF method to estimate AUV trajectory for turning and rotating motions. The simulation results show that the EKF method has an accuracy of more than 97% with a position.error of within the range of 0.05% - 3% and x position error of 0.0007325 meters, y position.error of 0.014337 m meters.