Micro-electro-mechanical system-based (MEMS-based) triaxial accelerometers are fundamental components of Inertial Measurement Units, and their use is widespread across various fields, such as the entertainment industry, robotics, and navigation systems. Various applications require that the cost of the sensor is not too high, which makes MEMS-based sensors a sensible choice. Unfortunately, low-cost MEMS are affected by relevant systematic errors which are time and environmental-condition dependent and thus require frequent re-calibration. Thus, simple calibration or identification methods, that a non-expert user can perform in the field without requiring costly equipment, are of interest. In this paper, we present an in-field identification procedure for MEMS-based triaxial accelerometers based on the linear Total Least Squares method.

Duchi M., Zaccaria F., Briot S., Ida E. (2023). Total Least Squares In-Field Identification for MEMS-Based Triaxial Accelerometers. Springer Science and Business Media B.V. [10.1007/978-3-031-45770-8_57].

Total Least Squares In-Field Identification for MEMS-Based Triaxial Accelerometers

Zaccaria F.
Secondo
Validation
;
Ida E.
Ultimo
Resources
2023

Abstract

Micro-electro-mechanical system-based (MEMS-based) triaxial accelerometers are fundamental components of Inertial Measurement Units, and their use is widespread across various fields, such as the entertainment industry, robotics, and navigation systems. Various applications require that the cost of the sensor is not too high, which makes MEMS-based sensors a sensible choice. Unfortunately, low-cost MEMS are affected by relevant systematic errors which are time and environmental-condition dependent and thus require frequent re-calibration. Thus, simple calibration or identification methods, that a non-expert user can perform in the field without requiring costly equipment, are of interest. In this paper, we present an in-field identification procedure for MEMS-based triaxial accelerometers based on the linear Total Least Squares method.
2023
Mechanisms and Machine Science
570
579
Duchi M., Zaccaria F., Briot S., Ida E. (2023). Total Least Squares In-Field Identification for MEMS-Based Triaxial Accelerometers. Springer Science and Business Media B.V. [10.1007/978-3-031-45770-8_57].
Duchi M.; Zaccaria F.; Briot S.; Ida E.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/955135
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