An IMM-Aided ZUPT Methodology for an INS/DVL Integrated Navigation System.

Area of Science:

• Robotics and Autonomous Systems
• Navigation and Positioning
• Ocean Engineering

Background:

• Inertial Navigation System (INS)/Doppler Velocity Log (DVL) integration is standard for underwater vehicle navigation.
• Underwater environments introduce errors in DVL velocity data, impacting navigation accuracy.
• Zero Velocity Update (ZUPT) technology effectively reduces INS errors in land vehicles but is challenging for underwater applications due to water currents.

Purpose of the Study:

• To propose an interactive multiple model (IMM)-aided ZUPT methodology for INS/DVL-integrated underwater navigation.
• To enhance navigation accuracy by effectively combining INS/DVL data with ZUPT principles.
• To address the limitations of direct ZUPT application in underwater environments.

Main Methods:

• Developed an IMM-aided ZUPT methodology for INS/DVL systems.
• Constructed parallel INS/DVL and INS/ZUPT models.
• Calculated model weights based on innovations and innovation covariance matrices.
• Evaluated the algorithm through simulations.

Main Results:

• The IMM-aided ZUPT solution demonstrated superior performance compared to standalone INS/DVL and INS/ZUPT solutions in underwater simulations.
• The proposed method accurately distinguished between ZUPT and non-ZUPT conditions.
• The algorithm's effectiveness was verified during simulated DVL outages.

Conclusions:

• The IMM-aided ZUPT methodology offers a significant improvement in underwater navigation accuracy for INS/DVL systems.
• This approach effectively mitigates errors caused by DVL inaccuracies and water currents.
• The proposed method provides a robust navigation solution, even under challenging conditions like DVL outages.