Detection of Magnetic Sensor Faults Based on Monocular Camera Images on Unmanned Aerial Vehicles Using Real Flight Data
Copyright (c) 2026 Jevuczó Gábor, Bauer Péter
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Abstract
Modern magnetometers integrated into inertial measurement units play a fundamental role
in control and navigation systems of unmanned aerial vehicles. Consequently, detecting their
failures is a key task for ensuring reliable navigation and to maintain flight safety. A promising
approach to solve this problem is to use the onboard cameras, as most modern drones come
equipped not just only with IMU and GNSS sensors but also with cameras for various tasks such as
video recordings. Accordingly, the objective of this work is to develop an algorithm for detecting
magnetic sensor failures using mono camera images. During this research, we developed an IMU
magnetometer fault detection method based on mono camera images and tested on real flight
data. The relative rotation of the camera between two consecutive frames was determined using
homography and essential matrices derived from the mono camera image sequence. Based on
the resulting cumulative rotation matrix, a method for detecting the magnetic sensor faults was
developed by applying an up-down counter-based residual thresholding method. Three different
types of sensor faults were artificially generated on the IMU’s magnetic measurements and the
proposed method successfully detected all three fault types.
Keywords:
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References
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