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The Application of Quaternions to Strap-Down MEMS Sensor Data.

Peter M Dickson1, Philip J Rae1

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This study details converting microelectromechanical systems (MEMS) sensor data using quaternions for tracking object motion during blast loading events. The method accurately animates complex rotations and displacements in the earth

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Area of Science:

  • Engineering
  • Physics
  • Data Science

Background:

  • Microelectromechanical systems (MEMS) sensors, including gyroscopes and accelerometers, are crucial for motion tracking.
  • Analyzing dynamic events like blast loading requires robust data processing techniques.
  • Complex rotations and displacements pose challenges for standard inertial data analysis.

Purpose of the Study:

  • To present mathematical transformations for converting 6-axis MEMS sensor data.
  • To enable accurate tracking of object motion during short-duration loading events.
  • To translate sensor data into a convenient earth frame of reference using quaternions.

Main Methods:

  • Utilized quaternion mathematics to describe object rotations and displacements.
  • Applied data conversion techniques to inertial data from MEMS sensor packages.
  • Focused on scenarios where inertial data alone is sufficient for motion tracking.

Main Results:

  • Successfully translated complex object motion into the earth frame of reference.
  • Demonstrated accurate tracking of an object subjected to strong air blast loading.
  • Generated an accurate animation of the object's subsequent motion.

Conclusions:

  • Quaternion-based data conversion is effective for analyzing MEMS sensor data in dynamic loading events.
  • The described method provides accurate motion tracking and visualization.
  • This approach facilitates a deeper understanding of object dynamics under extreme conditions.