On-site scale factor linearity calibration of MEMS triaxial gyroscopes

TL;DR

This paper presents a simple, field-friendly calibration method for MEMS triaxial gyroscopes using only a servo motor, leveraging gravity and rotational speed measurements to accurately determine scale factors.

Contribution

It introduces a novel calibration scheme that uses a fixed gravity vector and rotational speeds, simplifying the process with classical least squares and enabling effective field calibration.

Findings

The method accurately calibrates gyroscopes in simulations and experiments.

Experimental validation confirms the approach's effectiveness in real-world settings.

The approach streamlines calibration by eliminating complex procedures.

Abstract

The calibration of MEMS triaxial gyroscopes is crucial for achieving precise attitude estimation for various wearable health monitoring applications. However, gyroscope calibration poses greater challenges compared to accelerometers and magnetometers. This paper introduces an efficient method for calibrating MEMS triaxial gyroscopes via only a servo motor, making it well-suited for field environments. The core strategy of the method involves utilizing the fact that the dot product of the measured gravity and the rotational speed in a fixed frame remains constant. To eliminate the influence of rotating centrifugal force on the accelerometer, the accelerometer data is measured while stationary. The proposed calibration experiment scheme, which allows gyroscopic measurements when operating each axis at a specific rotation speed, making it easier to evaluate the linearity across a related speed range constituted by a series of rotation speeds. Moreover, solely the classical least squares algorithm proves adequate for estimating the scale factor, notably streamlining the analysis of the calibration process. Extensive numerical simulations were conducted to analyze the proposed method's performance in calibrating a triaxial gyroscope model. Experimental validation was also carried out using a commercially available MEMS inertial measurement unit (LSM9DS1 from Arduino nano 33 BLE SENSE) and a servo motor capable of controlling precise speed. The experimental results effectively demonstrate the efficacy of the proposed calibration approach.