Magnetometer Calibration for Small Unmanned Aerial Vehicles Using Cooperative Flight Data

Area of Science:

• Aerospace Engineering
• Robotics
• Navigation Systems

Background:

• Low-cost magnetometers on small Unmanned Aerial Vehicles (UAVs) often suffer from inaccurate heading angle estimates.
• Magnetic field disturbances from onboard electric equipment introduce systematic errors in magnetometer readings.
• Accurate heading estimation is critical for safe and effective UAV navigation and operation.

Purpose of the Study:

• To develop and present a new method for improving the accuracy of heading angle estimates from low-cost magnetometers on small UAVs.
• To address the challenge of systematic magnetic errors caused by onboard electronic equipment.
• To enable more reliable navigation for small UAVs through enhanced heading estimation.

Main Methods:

• The proposed method involves estimating systematic errors (magnetic biases) caused by onboard electric equipment.
• Calibration data is collected during in-flight operations under nominal thrust conditions to capture realistic magnetic disturbances.
• A chief UAV equipped with a visual camera tracks a cooperative deputy UAV, utilizing GNSS (Global Navigation Satellite System) for relative positioning to formulate a non-linear equation system for bias determination.

Main Results:

• The paper formulates the magnetic bias determination problem as a system of non-linear equations.
• The developed method allows for both off-line calibration using collected flight data and real-time on-board calibration.
• Experimental flight tests were conducted to assess the performance of the proposed calibration method.

Conclusions:

• The presented method effectively improves heading angle accuracy for small UAVs by addressing magnetic biases from onboard electronics.
• The approach leverages cooperative UAV operations, visual tracking, and GNSS data for robust calibration.
• The findings support the potential for both off-line and real-time implementation, enhancing UAV navigation capabilities.