Attitude Estimation of AUVs Based on a Network of Pressure Sensors

Underwater navigation is a challenging task for Autonomous Underwater Vehicles (AUVs), which requires to estimate the position and orientation of the vehicle. Accelerometer-based attitude estimation is problematic as its accuracy can degrade by up to two orders of magnitude when the AUV is accelerating. Pressure sensors, which are unaffected by acceleration, offer an efficient alternative for determining orientation. This paper offers a method for pitch-and-roll estimation using a network of pressure sensors and a thorough analysis of the method's accuracy including analytical evaluation and the Cramér-Rao lower bound. Then, the method is tested in a simulation. We also provide a way to estimate system performance based on the vehicle's size and the number and accuracy of the sensors.