Path planning of autonomous underwater vehicle for optimal acoustic tomography

Ocean acoustic tomography (OAT) can infer the state of the interior of the survey domain from measurements along the periphery. Traditionally, a network of mooring platforms with projector/hydrophone array is deployed, sometimes combined with moving vessel nodes. In this paper we look at the OAT problem with autonomous underwater vehicle (AUV) equipped with a hydrophone as a moving receiver and study the AUV path-planning techniques to optimize the tomographic measurements. The path planning problem is to find the optimal AUV depths that minimize the sound speed profile posterior uncertainty along its path under the AUV navigation constraint. Numeric simulation results are shown to confirm the effectiveness of the approach.