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An Inertial Measurement Unit Based Method to Estimate Hip and Knee Joint Kinematics in Team Sport Athletes on the Field
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Enhanced Autonomous Vehicle Positioning Using a Loosely Coupled INS/GNSS-Based Invariant-EKF Integration.

Ahmed Ibrahim1, Ashraf Abosekeen1, Ahmed Azouz1

  • 1Electrical Engineering Branch, Military Technical College (MTC), Cairo 11766, Egypt.

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Summary
This summary is machine-generated.

This study enhances autonomous vehicle navigation by integrating inertial navigation systems (INS) with Global Navigation Satellite Systems (GNSS) using an invariant extended Kalman filter (IEKF). The IEKF significantly improves positioning accuracy, especially during GNSS signal loss.

Keywords:
EKFGNSSIEKFINSINS/GNSS integrationMEMS-IMUnavigationpositioning

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Area of Science:

  • Robotics and Autonomous Systems
  • Navigation and Positioning
  • Signal Processing

Background:

  • High-precision navigation is crucial for autonomous vehicles (AVs).
  • Global Navigation Satellite Systems (GNSS) offer primary navigation but suffer signal degradation in certain environments.
  • Inertial Navigation Systems (INS) provide continuous navigation but drift over time.

Purpose of the Study:

  • To introduce and validate a loosely coupled INS/GNSS integration scheme using the invariant extended Kalman filter (IEKF).
  • To address the limitations of traditional Extended Kalman Filter (EKF) based INS/GNSS integration, particularly in GNSS-deprived scenarios.

Main Methods:

  • Implemented a loosely coupled INS/GNSS integration framework.
  • Utilized the invariant extended Kalman filter (IEKF), leveraging matrix Lie group for state estimation.
  • Tested the proposed system on a real-world road trajectory.

Main Results:

  • The IEKF-based INS/GNSS integration demonstrated significant performance enhancement over traditional EKF methods.
  • Achieved an 82.98% improvement in overall trajectory 2D-position Root Mean Square (RMS) error (19.4m to 3.3m).
  • Reduced the 2D-position maximum error by 80.78% (73.9m to 14.2m).

Conclusions:

  • The IEKF-based INS/GNSS integration offers superior navigation accuracy and robustness compared to EKF methods.
  • This approach is effective in both GNSS signal presence and blockage conditions, crucial for AV reliability.