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A Novel Calibration Method for Gyro-Accelerometer Asynchronous Time in Foot-Mounted Pedestrian Navigation System.

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This study addresses asynchronous sensor timing in pedestrian navigation systems (PNS) using micro-electro-mechanical inertial measurement units (MIMU). A new error model and filtering method improve positioning accuracy by calibrating sensor time differences.

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calibration methoderror modelgyro-accelerometer asynchronous timepedestrians navigation systemzero-velocity detection

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Area of Science:

  • Navigation Systems
  • Sensor Fusion
  • Inertial Navigation

Background:

  • Indoor positioning in Global Navigation Satellite System (GNSS)-denied environments is challenging.
  • Pedestrian Navigation Systems (PNS) often rely on Micro-Electro-Mechanical Inertial Measurement Units (MIMU).
  • Asynchronous sampling between gyroscopes and accelerometers in MIMU degrades PNS positioning accuracy.

Purpose of the Study:

  • To develop a novel error model for gyro-accelerometer asynchronous time in foot-mounted PNS.
  • To analyze the impact of sensor time asynchrony on pedestrian navigation performance.
  • To propose a filtering method for calibrating asynchronous sensor timing and enhance PNS accuracy.

Main Methods:

  • Development of a new error model for gyro-accelerometer asynchronous time.
  • Analysis of the effects of asynchronous sensor timing on pedestrian navigation.
  • Design of a filtering model for real-time calibration of sensor time asynchrony.
  • Implementation of a zero-velocity detection method based on attitude change rate.

Main Results:

  • Effective estimation of gyro-accelerometer asynchronous time was achieved.
  • The proposed filtering method successfully calibrated sensor time differences.
  • Positioning accuracy of the PNS was significantly improved after error compensation.

Conclusions:

  • Gyro-accelerometer asynchronous time is a critical error source in MIMU-based PNS.
  • The developed error model and filtering approach effectively mitigate positioning errors.
  • The proposed method enhances the reliability and accuracy of indoor pedestrian navigation systems.