Analysis and Self-Calibration Method for Asynchrony between Sensors in Rotation INS

Area of Science:

• Navigation Systems Engineering
• Sensor Fusion Technology
• Inertial Measurement Units

Background:

• Dual-axis rotation inertial navigation systems (RINS) rely on gyroscopes, accelerometers, and angular encoders.
• Sensor asynchronies are a critical challenge, leading to significant navigation errors.
• Understanding the impact of specific sensor timing mismatches is crucial for RINS accuracy.

Purpose of the Study:

• To analyze the impact of asynchrony between the gyroscope and angular encoder on azimuth error in RINS.
• To investigate the effect of asynchrony between the gyroscope and accelerometer on velocity error in RINS.
• To propose and validate a self-calibration method to mitigate these navigation errors.

Main Methods:

• Mathematical analysis of sensor asynchrony effects on RINS performance metrics (azimuth and velocity errors).
• Development of a novel self-calibration algorithm leveraging navigation error data.
• Experimental validation of the proposed self-calibration method using real-world sensor data.

Main Results:

• Quantified the specific contributions of gyroscope-encoder and gyroscope-accelerometer asynchronies to azimuth and velocity errors, respectively.
• Demonstrated that the proposed self-calibration method effectively compensates for sensor timing deviations.
• Experimental results confirmed significant improvements in both azimuth and velocity accuracy after applying the compensation.

Conclusions:

• Sensor asynchrony is a key factor limiting RINS accuracy, particularly affecting azimuth and velocity.
• The developed self-calibration method offers a practical solution for improving RINS performance.
• Compensating for sensor asynchronies is essential for achieving high-accuracy dual-axis rotation inertial navigation.