Set-membership acoustic tracking of autonomous underwater vehicles

A set-membership algorithm is presented for tracking of Autonomous Underwater Vehicles (AUVs) from acoustic time-of-flight measurements received by a field of surface floating buoys. The algorithm assumes that measurement errors and AUV dynamics uncertainties are of unknown but bounded magnitude, with known bounds, and produces as output the set of admissible AUV positions. The proposed procedure has been validated by simulations in which uncertainty models have been obtained from field data at sea. Tracking performance is shown superior than that of the Extended Kalman Filter (EKF) in presence of biased disturbances.