Development of a navigation algorithm for autonomous underwater vehicles

In this paper, the authors present an underwater navigation system for Autonomous Underwater Vehicles (AUVs) which exploits measurements from an Inertial Measurement Unit (IMU), a Pressure Sensor (PS) for depth and the Global Positioning System (GPS, used during periodic and dedicated resurfacings) and relies on either the Extended Kalman Filter (EKF) or the Unscented Kalman Filter (UKF) for the state estimation. Both (EKF and UKF) navigation algorithms have been validated through experimental navigation data related to some sea tests performed in La Spezia (Italy) with one of Typhoon class vehicles during the NATO CommsNet13 experiment (held in September 2013) and through Ultra-Short BaseLine (USBL) fixes used as a reference (ground truth). Typhoon is an AUV designed by the Department of Industrial Engineering of the Florence University for exploration and surveillance of underwater archaeological sites in the framework of the Italian THESAURUS project and the European ARROWS project. The obtained results have demonstrated the effectiveness of both navigation algorithms and the superiority of the UKF (very suitable for AUV navigation and, up to now, still not used much in this field) without increasing the computational load (affordable for on-line on-board AUV implementation).