Filtering Depth Measurements in Underwater Vehicles for Improved Seabed Imaging

Underwater vehicles are commonly used for detailed seabed mapping. To derive a bathymetric map, the depth of the underwater vehicle must be known. The offshore survey industry has often strong requirements on both absolute and relative accuracy. Depth is usually deduced from a measurement of absolute pressure. Regardless of the quality of the pressure sensor, the pressure measurement is influenced by environmental factors, such as waves, tide, atmospheric pressure and sea water density profile. In the paper we analyze these factors with respect to their behavior and effect on the measured depth. An underwater vehicle equipped with an aided inertial navigation system (AINS) has through its accelerometers and Doppler velocity log redundant information on the movement of the underwater vehicle. Using this information, an AINS is well suited to filter out dynamic pressure sensor noise. Linear wave theory is used to model the effects of the waves on the pressure sensor, and it is suggested how the parameters of the pressure sensor noise model can be deduced from the mean wave amplitude and period. AINS performance is often substantially improved by post-processing. The paper will therefore examine the depths outputted from the pressure sensor, from the AINS real-time filter, and from post processing the AINS measurements.