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Updated: Jul 5, 2025

An Inertial Measurement Unit Based Method to Estimate Hip and Knee Joint Kinematics in Team Sport Athletes on the Field
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A Fast Self-Calibration Method for Dual-Axis Rotational Inertial Navigation Systems Based on Invariant Errors.

Xin Sun1, Jizhou Lai1, Pin Lyu1

  • 1Navigation Research Center, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China.

Sensors (Basel, Switzerland)
|January 23, 2024
PubMed
Summary

This study presents a new self-calibration method for dual-axis rotational inertial navigation systems (RINSs). The automated approach calibrates inertial measurement units (IMUs) without disassembly, improving accuracy and reducing calibration time.

Keywords:
backtracking navigationdual-axis rotational inertial navigation systeminvariant errorsobservability analysissystem-level self-calibration

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Area of Science:

  • Navigation Systems Engineering
  • Mechatronics and Control Systems
  • Geomatics and Surveying

Background:

  • Dual-axis rotational inertial navigation systems (RINSs) require periodic calibration for sustained accuracy.
  • Traditional inertial measurement unit (IMU) calibration is labor-intensive, time-consuming, and risks introducing new installation errors.
  • Existing methods necessitate equipment disassembly, hindering operational readiness.

Purpose of the Study:

  • To develop a system-level, automated self-calibration method for RINSs that eliminates the need for disassembly.
  • To enable high-precision calibration by utilizing invariant error modeling.
  • To significantly reduce calibration time and improve the overall accuracy of RINS.

Main Methods:

  • Expressing navigation parameter errors in the inertial frame as invariant errors for rapid and accurate initial attitude estimation.
  • Establishing angular velocity constraint equations using gimbal mechanism output and employing backtracking navigation to reuse sensor data.
  • Designing a specific IMU rotation scheme to ensure full error observability, analyzed via piecewise constant system methods and singular value decomposition (SVD).

Main Results:

  • The proposed method effectively estimates IMU errors and rotation axis installation errors within 12 minutes.
  • Achieved estimation accuracy for errors is less than 4%.
  • Post-calibration compensation significantly enhances the velocity and position accuracies of the RINS.

Conclusions:

  • The developed self-calibration technique offers a highly efficient and accurate solution for RINS maintenance.
  • Automated, in-situ calibration without disassembly is feasible and beneficial for RINS performance.
  • This method addresses the limitations of traditional calibration, improving operational efficiency and navigational precision.