An Improved Fast Self-Calibration Method for Hybrid Inertial Navigation System under Stationary Condition.

Area of Science:

• Navigation Systems
• Sensor Calibration
• Inertial Measurement Units

Background:

• Inertial navigation system (INS) accuracy depends heavily on inertial measurement unit (IMU) calibration.
• Classical calibration methods often require high-precision turntables, increasing cost and complexity.
• Gyro drifts and accelerometer biases are key error sources affecting INS performance.

Purpose of the Study:

• To present a continuous dynamic self-calibration method for hybrid inertial navigation systems (HINS).
• To reduce the reliance on high-precision turntables in IMU calibration.
• To accurately identify all error parameters of HINS.

Main Methods:

• Established error models for accelerometers and gyros using a suitable IMU frame.
• Utilized navigation errors during rolling as observations.
• Calculated intermediate parameters to identify the twenty-one error parameters of HINS.

Main Results:

• The proposed method successfully identified all twenty-one error parameters of HINS.
• Experimental verification confirmed accuracy equivalent to classical calibration methods.
• The method demonstrated efficiency, simplicity, and feasibility.

Conclusions:

• The continuous dynamic self-calibration method is a viable alternative for HINS calibration.
• This approach offers comparable accuracy to traditional methods with reduced equipment requirements.
• The technique provides a rapid, simple, and feasible solution for improving INS navigation accuracy.