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. 2024 Sep 6;24(17):5795.
doi: 10.3390/s24175795.

A Novel Method and System Implementation for Precise Estimation of Single-Axis Rotational Angles

Qinghua Yang  1 , Yang Shen  1 , Xuetao Sun  1 , Changfa Wang  1   2
Affiliations

A Novel Method and System Implementation for Precise Estimation of Single-Axis Rotational Angles

Qinghua Yang et al. Sensors (Basel). .

Abstract

Accurately estimating single-axis rotational angle changes is crucial in many high-tech domains. However, traditional angle measurement techniques are often constrained by sensor limitations and environmental interferences, resulting in significant deficiencies in precision and stability. Moreover, current methodologies typically rely on fixed-axis rotation models, leading to substantial discrepancies between measured and actual angles due to axis misalignment. To address these issues, this paper proposes an innovative method for single-axis rotational angle estimation. It introduces a calibration technique for installation errors between inertial measurement units and the overall measurement system, effectively translating dynamic rotational inertial outputs to system enclosure outputs. Subsequently, the method employs triaxial accelerometers combined with zero-velocity detection technology to estimate the rotation axis position. Finally, it delves into analyzing the relationship between quaternion and axis-angle, aimed at reducing noise interference for precise rotational angle estimation. Based on this proposed methodology, a Low-Cost, a High Accuracy Measurement System (HAMS) integrating sensor fusion was designed and implemented. Experimental results demonstrate static measurement errors below ±0.15° and dynamic measurement errors below ±0.5° within a ±180° range.

Keywords: angle measurement; axis–angle pair; calibration; inertial measurement unit.

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Conflict of interest statement

Author Changfa Wang was employed by the company Shanghai Aircraft Manufacturing Co., Ltd. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
The relationship between the HAMS coordinate frame S and the IMU coordinate system I.
Figure 2
Figure 2
The block diagram of the algorithm system.
Figure 3
Figure 3
Changes in acceleration data during stillness and motion.
Figure 4
Figure 4
Changes in angular velocity data during stillness and motion.
Figure 5
Figure 5
Changes in angular data during stillness and motion.
Figure 6
Figure 6
Schematic of the rotation axis direction in the geodetic coordinate system.
Figure 7
Figure 7
Comparison experiment of different thresholds for rotational components.
Figure 8
Figure 8
HAMS and AHRS Experimental.
Figure 9
Figure 9
Angular velocity data in static experiment.
Figure 10
Figure 10
Angle comparison in static characteristic experiment.
Figure 11
Figure 11
IOE error in static experiment.
Figure 12
Figure 12
Our method’s error in static experiment.
Figure 13
Figure 13
Angular velocity data in dynamic experiment.
Figure 14
Figure 14
Angle comparison in dynamic characteristic experiment.
Figure 15
Figure 15
IOE error in dynamic experiment.
Figure 16
Figure 16
My Method error in dynamic experiment.
Figure 17
Figure 17
Angular velocity data in system experiment.
Figure 18
Figure 18
Angle comparison in system experiment.
Figure 19
Figure 19
AHRS error in system experiment.
Figure 20
Figure 20
HAMS error in system experiment.
See this image and copyright information in PMC

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