AUV Underwater Positioning Algorithm Based on Interactive Assistance of SINS and LBL

Area of Science:

• Marine robotics and navigation
• Underwater acoustics and signal processing
• Inertial navigation systems

Background:

• Accurate underwater positioning is critical for Autonomous Underwater Vehicle (AUV) operations.
• Traditional methods like dead reckoning suffer from cumulative errors.
• Multipath transmission of acoustic signals complicates underwater localization.

Purpose of the Study:

• To develop an advanced underwater positioning algorithm.
• To enhance the accuracy and reliability of AUV navigation.
• To extend the operational duration of AUVs in underwater environments.

Main Methods:

• Integration of strapdown inertial navigation system (SINS) with Long Baseline (LBL) positioning.
• Implementation of an optimal correlation algorithm aided by SINS/Doppler Velocity Log (DVL)/Magnetic Compass Pilot (MCP).
• Application of a 3D Time Difference of Arrival (TDOA) positioning algorithm using Taylor series expansion.
• Utilization of a multi-sensor information fusion algorithm.

Main Results:

• The proposed algorithm effectively corrects cumulative errors from dead reckoning.
• It successfully resolves ambiguous correlation peaks caused by underwater acoustic multipath effects.
• Simulation results demonstrate superior performance compared to traditional underwater positioning algorithms.

Conclusions:

• The developed algorithm offers a direct and effective method for calibrating AUV position errors.
• This advancement significantly improves the precision and robustness of underwater navigation.
• The enhanced positioning capability leads to prolonged underwater mission durations for AUVs.