Bias Estimation for Low-Cost IMU Including X- and Y-Axis Accelerometers in INS/GPS/Gyrocompass.

Area of Science:

• Navigation and Positioning Systems
• Sensor Technology
• Maritime Engineering

Background:

• Inertial Navigation Systems (INSs) offer autonomous positioning but traditional high-cost sensors limit adoption.
• Low-cost Micro-Electro-Mechanical Systems (MEMS)-based Inertial Measurement Units (IMUs) suffer from accuracy and bias issues, especially in maritime settings.
• Accurate INS are crucial for reliable maritime navigation, particularly when Global Navigation Satellite Systems (GNSSs) are unavailable.

Purpose of the Study:

• To develop an improved bias estimation method for low-cost IMUs in INS.
• To enhance the accuracy of position and attitude estimation for maritime navigation.
• To provide a cost-effective alternative to traditional high-cost INS sensors.

Main Methods:

• Proposed an improved bias estimation technique by comparing trajectory generator (TG) estimations with actual measurements.
• Introduced an altitude-difference correlation method using INS/GNSS/gyrocompass (IGG) data for X and Y-axis acceleration bias estimation.
• Validated methods using simulation datasets with statistical analyses including FFT and Butterworth filter for angular velocity bias.

Main Results:

• The Butterworth filter demonstrated the lowest angular-velocity bias estimation error.
• Altitude-based estimation for X and Y-axis acceleration bias yielded differences of 1.2 × 10⁻² m/s² and 1.0 × 10⁻⁴ m/s² respectively, using 30 minutes of data.
• The proposed methods significantly enhance the accuracy of low-cost IMUs for maritime navigation.

Conclusions:

• The developed bias estimation techniques effectively improve the performance of low-cost IMUs.
• This research presents a viable, cost-effective solution for accurate maritime navigation.
• Enhanced INS accuracy using MEMS IMUs opens possibilities for broader adoption in marine applications.