Dynamic parameters identification for a longitudinal model of an AUV exploiting experimental data

This work addresses the problem of determining a low cost method to identify the dynamic parameters of the surge motion model for an Autonomous Underwater Vehicle (AUV) utilising experimental data. With this goal, various sea tests were planned and carried out, involving minimal equipment. In particular, an acoustic tracking system composed of passive Direction of Arrival (DoA) sensors was used to track the vehicle while moving underwater. Such dataset was exploited to identify the values of the dynamic parameters with a best fit approach. Eventually, the comparison between the signals computed through the identified model and the experimental data has been reported as a preliminary evaluation.