Attitude Estimation of Underwater Vehicles Using Field Measurements and Bias Compensation

Area of Science:

• Robotics
• Navigation Systems
• Geophysics

Background:

• Underwater vehicle attitude estimation is crucial for navigation.
• Existing methods using Euler angles suffer from reduced yaw accuracy due to measurement uncertainties.
• Previous approaches often simplify magnetic field measurements, neglecting full vector components.

Purpose of the Study:

• To propose a new method for estimating underwater vehicle attitude.
• To overcome the limitations of existing methods regarding yaw accuracy and measurement assumptions.
• To enhance the utilization of gravitational and magnetic field vector measurements.

Main Methods:

• Utilizing both gravitational and magnetic field vectors in their entirety, without conversion to Euler angles.
• Estimating and compensating for bias in the measured magnetic field vector.
• Processing measured field vectors independently to mitigate error propagation.

Main Results:

• The proposed method demonstrates improved attitude estimation accuracy.
• Independent processing of vector components reduces the cumulative effect of measurement uncertainties.
• Experimental validation with an unmanned underwater vehicle confirmed the method's efficacy.

Conclusions:

• The novel attitude estimation method offers enhanced accuracy for underwater vehicles.
• By leveraging full field vector components and bias compensation, it surpasses traditional Euler angle-based approaches.
• This technique provides a more robust solution for underwater navigation systems.