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Research on IMU Calibration Model Based on Polar Decomposition.

Guiling Zhao1, Maolin Tan1, Xu Wang1

  • 1School of Geomatics, Liaoning Technical University, Fuxin 123000, China.

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|March 29, 2023
PubMed
Summary

This study introduces a new inertial measurement unit (IMU) calibration model to improve strapdown inertial navigation system (SINS) accuracy. The novel method effectively compensates for installation errors, significantly enhancing navigation performance.

Keywords:
IMUcalibrationinstallation error modelmisalignment errornonorthogonal errorpolar decomposition

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Area of Science:

  • Navigation Systems Engineering
  • Geomatics Engineering
  • Aerospace Engineering

Background:

  • Inertial Measurement Units (IMUs) are crucial for Strapdown Inertial Navigation Systems (SINS).
  • Installation errors in IMUs significantly degrade SINS navigation accuracy, especially in dynamic environments.
  • Existing calibration models may not fully address complex installation error components.

Purpose of the Study:

  • To propose a novel IMU calibration model based on polar decomposition to address installation errors.
  • To decompose and compensate for nonorthogonal and misalignment errors in IMUs.
  • To develop and validate a simplified installation error model for enhanced SINS performance.

Main Methods:

  • Utilized polar decomposition to model IMU installation errors.
  • Decomposed installation error into nonorthogonal and misalignment components for sequential compensation.
  • Employed a three-axis turntable for calibrating SINS with the proposed model.
  • Developed a simplified installation error matrix based on experimental findings.

Main Results:

  • Experimental calibration revealed misalignment errors to be larger than nonorthogonal errors.
  • The proposed simplified calibration model demonstrated superiority over traditional methods.
  • Navigation experiments showed significant improvements in attitude, velocity, and position accuracy.

Conclusions:

  • The polar decomposition-based IMU calibration model effectively compensates for installation errors.
  • A simplified installation error model derived from experimental results offers superior navigation accuracy.
  • The proposed method enhances SINS performance in terms of attitude, velocity, and position accuracy.