A forward-looking SONAR and dynamic model-based AUV navigation strategy: Preliminary validation with FeelHippo AUV

摘要

Reliable navigation systems are fundamental for Autonomous Underwater Vehicles (AUVs) to perform complex tasks and missions. It is well known that the Global Positioning System (GPS) cannot be employed in underwater scenarios; thus, during missions below the sea's surface the real-time position is usually obtained with expensive sensors, such as the Doppler Velocity Log (DVL), integrated within a navigation filter such as an Extended Kalman Filter (EKF), Unscented Kalman Filter (UKF), or Dead Reckoning (DR) strategies. The goal of this work is to develop an underwater navigation system that does not rely on a DVL and where linear speed estimations are obtained exploiting data from a Forward-Looking SONAR (FLS) or, in its absence, taking advantage of a dynamic model that presents a reduced set of parameters. The proposed solution is validated through the use of navigation data obtained during sea trials undertaken in July 2018 with FeelHippo AUV at La Spezia (Italy), at the NATO Science and Technology Organization Center for Maritime Research and Experimentation (CMRE).