Towards Enhancing the Navigational Accuracy of UUVs Through Collaboration of Multiple Heterogeneous Marine Vehicles

A modular measurement model Extended Kalman filter (EKF) for for unmanned underwater vehicle (UUV) localization is proposed. Except for using measurements from UUV's sensors, this EKF is augmented by ultra-short baseline range and visual-data based localization from an unmanned surface vehicle, and in-sonar image estimated UUV position. It is shown that the proposed EKF significantly enhances UUV's navigational accuracy through a collaborative fusion of sensor data from multiple heterogeneous marine vehicles. Also, an Extended Rauch-Tung-Striebel (ERTS) smoother was run aposteriori to further improve UUV's localization, which is shown to be very useful for accurate post-processing of the data acquired by the UUV.