Analysis, verification and optimization of AUV navigation using underwater acoustic models

Autonomous Underwater Vehicles (AUV) are becoming significant in many underwater applications due to accessibility, autonomous features and data collection functionalities. In order to achieve greater operational efficiency, there is a need of effective techniques for self-localization and tracking of the vehicles. In the current AUVs, long base line (LBL) techniques are used for localization. LBL techniques use acoustic ranging between the transponders (at known locations) and the AUVs. The acoustic signals are greatly affected by different underwater environment parameters, therefore it is necessary to study their impacts on the acoustic signal propagation. Some of the parameters include water column temperature, salinity, depth and source-receiver configuration. In this paper these environmental effects are studied using acoustic models and compared with the AUV data obtained from the experiment at the Trondheim Fjord in April 2015. The real data and the simulated data show good match which proves that the LBL acoustic signals are affected by the environment. An environmental parameter analysis is also presented, using the acoustic model, to show the effect of sound speed profile and transponder depth on the acoustic signals. The results show that the sound speed profile has great impact on acoustic signal propagation and the transponder depth should be selected based on the sound speed profile to achieve better performance. Therefore, the environmental parameters should be considered for effective path planning and optimizing the navigation performance of the AUV.