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Foot-Mounted Pedestrian Navigation Method by Comparing ADR and Modified ZUPT Based on MEMS IMU Array.

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Summary

This study introduces an adaptive deck reckoning (ADR) and modified zero velocity update (ZUPT) framework using Micro-Electro-Mechanical Systems (MEMS) Inertial Measurement Unit (IMU) arrays to enhance pedestrian navigation system (PNS) accuracy.

Keywords:
MEMS IMU arrayadaptive dead reckoning (ADR)pedestrian navigationzero velocity update (ZUPT)

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Area of Science:

  • Robotics
  • Sensor Fusion
  • Navigation Systems

Background:

  • Pedestrian navigation systems (PNS) often rely on Micro-Electro-Mechanical Systems (MEMS) Inertial Measurement Unit (IMU) arrays for tracking.
  • Improving the accuracy of pedestrian tracking remains a challenge in PNS development.
  • Existing methods like maximum likelihood estimator (MLE) fusion have limitations in handling drift errors.

Purpose of the Study:

  • To propose a novel integrated framework combining adaptive deck reckoning (ADR) with modified zero velocity update (ZUPT) for enhanced pedestrian tracking.
  • To improve the accuracy of distance calculation and overall positioning in pedestrian navigation.
  • To adaptively fuse readings from MEMS IMU arrays, outperforming traditional methods.

Main Methods:

  • Development of an in-house MEMS IMU array.
  • Implementation of an ADR algorithm to identify and remove IMUs with significant drift errors based on step length and track angle.
  • Estimation of foot position using least squares (LS) with data from remaining IMUs, integrated with modified ZUPT.

Main Results:

  • The ADR/modified ZUPT method demonstrated significantly closer end-position accuracy to reference trajectories in straight-line experiments compared to MLE.
  • Closed-loop track experiments (approx. 300 m) showed positioning errors less than 0.6% (1σ) for the proposed method.
  • The proposed method achieved superior accuracy over MLE, which exhibited positioning errors exceeding 1% (1σ).

Conclusions:

  • The proposed ADR and modified ZUPT framework effectively enhances pedestrian tracking accuracy in PNS.
  • Adaptive fusion of IMU array readings provides a more robust solution for navigation compared to traditional averaging methods.
  • This approach offers a significant improvement in positioning accuracy for pedestrian navigation applications.