Measuring Tilt with an IMU Using the Taylor Algorithm

Author:

Demkowicz Jerzy1

Affiliation:

1. Department of Geoinformatics, Faculty of Electronics, Telecommunications and Informatics, Gdańsk University of Technology, 80-233 Gdańsk, Poland

Abstract

This article addresses the important problem of tilt measurement and stabilization. This is particularly important in the case of drone stabilization and navigation in underwater environments, multibeam sonar mapping, aerial photogrammetry in densely urbanized areas, etc. The tilt measurement process involves the fusion of information from at least two different sensors. Inertial sensors (IMUs) are unique in this context because they are both autonomous and passive at the same time and are therefore very attractive. Their calibration and systematic errors or bias are known problems, briefly discussed in the article due to their importance, and are relatively simple to solve. However, problems related to the accumulation of these errors over time and their autonomous and dynamic correction remain. This article proposes a solution to the problem of IMU tilt calibration, i.e., the pitch and roll and the accelerometer bias correction in dynamic conditions, and presents the process of calculating these parameters based on combined accelerometer and gyroscope records using a new approach based on measuring increments or differences in tilt measurement. Verification was performed by simulation under typical conditions and for many different inertial units, i.e., IMU devices, which brings the proposed method closer to the real application context. The article also addresses, to some extent, the issue of navigation, especially in the context of dead reckoning.

Publisher

MDPI AG

Reference34 articles.

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2. Demkowicz, J. (2018, January 4–6). Autonomous Vehicle Navigation in Dense Urban Area in Global Positioning Context. Proceedings of the 2018 11th International Conference on Human System Interaction (HSI), Gdansk, Poland.

3. ASG-EUPOS (2024, February 17). EUPOS, System Description. Reference Stations. Available online: http://www.asgeupos.pl/.

4. Yeong, J., Velasco-Hernandez, G., Barry, J., and Walsh, J. (2021). Sensor and Sensor Fusion Technology in Autonomous Vehicles: A Review. Sensors, 21.

5. Groves, P.D. (2013). Principles of GNSS, Inertial, and Multisensor Integrated Navigation Systems, Artech House.

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