Abstract

Autonomous underwater vehicles localization and navigation are challenging due to the lack of Global Positioning System underwater: alternative techniques have then to be used in order to measure the position of the vehicle. To this aim, sensor fusion methods based on acoustic positioning systems are often exploited. This article faces the study and the improvement of the localization of an underwater target through an ultra short baseline–aided buoy built by the Mechatronics and Dynamic Modelling Laboratory of the University of Florence. Such a buoy relies on an ultra short baseline device for the localization and is aided by a proper sensor set in order to compensate variations in its pose. First, a study of the underwater localization based on the ultra short baseline technique is provided. The measurement errors entailed by the buoy motion are then analyzed and preliminarily compensated, exploiting linear least squares methods. Subsequently, filtering techniques are considered with the aim to further increase the accuracy of the ultra short baseline measurements. Due to the nonlinearities of the sensors characteristics, extended Kalman filter has been used, with different models for stationary and moving targets. The solutions proposed have been validated through experimental tests conducted with MArine Robotic Tool for Archaeology autonomous underwater vehicles built by the Mechatronics and Dynamic Modelling Laboratory. The results evidence an improved vehicle localization, suggesting interesting future developments concerning both mechanical and computational solutions.

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