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A New Quaternion-Based Kalman Filter for Real-Time Attitude Estimation Using the Two-Step Geometrically-Intuitive

Kaiqiang Feng1,2, Jie Li3,4, Xiaoming Zhang5,6

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Summary

This study introduces a novel Kalman filter for attitude heading reference systems (AHRS) to improve pitch/roll estimation accuracy during magnetic distortion. The new method reduces computational load and enhances performance in challenging conditions.

Keywords:
AHRSKalman filterattitude estimationmagnetic distortiontwo-step geometrically intuitive correction (TGIC)

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Area of Science:

  • Navigation Systems
  • Sensor Fusion
  • Control Theory

Background:

  • Low-cost Attitude Heading Reference Systems (AHRS) often struggle with pitch/roll estimation accuracy due to magnetic distortions.
  • Existing methods can suffer from high computational complexity and linearization errors in measurement equations.

Purpose of the Study:

  • To propose a novel linear Kalman filter algorithm for nonlinear attitude estimation.
  • To enhance the pitch/roll estimation accuracy and reduce computational complexity of AHRS under magnetic distortion.

Main Methods:

  • A new algorithm combining a two-step geometrically-intuitive correction (TGIC) with a Kalman filter is presented.
  • The TGIC scheme sequentially corrects pitch/roll estimation, making it immune to magnetic distortion.
  • TGIC provides a computed quaternion input to the Kalman filter, avoiding linearization errors and reducing complexity.

Main Results:

  • Experimental validation demonstrates significant performance improvements.
  • Mean time consumption was reduced by 45.9% compared to standard filters.
  • Root Mean Square Error (RMSE) for pitch/roll estimation under magnetic disturbances decreased by 33.8%.

Conclusions:

  • The proposed filter effectively improves pitch/roll estimation accuracy in the presence of magnetic distortion.
  • The algorithm offers reduced computational complexity and is suitable for various dynamic conditions.
  • This approach enhances the reliability and efficiency of low-cost AHRS.