A model aided inertial navigation system with a low acoustic signature for localization of surveillance AUVs

Localization and navigation systems with a lower acoustic signature is a requisite for autonomous underwater vehicles (AUVs) carrying out surveillance operations, which is a challenging task due to limited availability of sensors. Utilizing inertial navigation systems (INSs) is one of the options, although it still presents a certain degree of position drift, even with a high-grade INS. This study investigates the capability of a model-aided inertial navigation system (MA-INS) with limited activation of Doppler velocity log (DVL) acoustic sensor to localize AUVs. Employing a Kalman filter (KF) data fusion algorithm, the acceleration measurements from the INS and the vehicle velocities predicted by a motion response predicting mathematical model were combined with intermittent DVL measurements. The acoustic signature was reduced while maintaining a reliable localization accuracy. These findings show that localization of surveillance AUVs can be conducted by the MA-INS algorithm with a minimized DVL usage. As the DVL operating time could be controlled by the DVL application schemes, the algorithm could be optimized depending on the planned routes of AUV during the field trial. However, considerable investigation may be needed to obtain highly accurate localization solution using non-acoustic sensors. For future work, it is recommended to impeccably restrain the use of DVL for the localization, in order to secure the concealment of AUV from detection.