An algorithm to estimate positions, orientations, linear velocities and angular rates of an Underwater Remotely Operated Vehicle (UROV), based on the Extended Kalman Filter (EKF), is presented. The complete UROV kinematic and dynamic models are combined to obtain the process equation, and measurements correspond to linear accelerations and angular rates provided by an Inertial Measurement Unit (IMU). The proposed algorithm is numerically validated and its results are compared with simulated UROV states. A
