A Pretreatment Method for the Velocity of DVL Based on the Motion Constraint for the Integrated SINS/DVL

Abstract

It is difficult for autonomous underwater vehicles (AUVs) to obtain accurate aided position information in many locations because of underwater conditions. The velocity accuracy from the Doppler velocity log (DVL) is a key element in deciding the AUV position accuracy when the integration system of Strapdown Inertial Navigation System/DVL/Magnetic Compass/Press Sensor (SINS/DVL/MCP/PS) is adopted. However, random noise and sudden noise in DVL caused by sound scattering, fishing populations, and seafloor gullies introduce level attitude errors and accumulate as position error. To restrain random noise, a velocity tracing method is designed based on the constant velocity model and the assumption of slow motion of AUV. To address sudden noise, a fault diagnosis method based on the χ 2 rule is introduced to judge sudden changes from innovation. When a sudden change occurs, the time update of the velocity from the tracing model is used for data fusion instead of the velocity from DVL. Simulation test results indicate that with this velocity tracing algorithm, random noise in the DVL can be effectively restrained. The level attitude accuracy and the level position accuracy are also improved with the time update of the velocity when the sudden change occurs.

Keywords

• AUV
• SINS/DVL/MCP/PS integrated navigation system
• velocity tracing
• constant velocity motion model
• Kalman filter