Enhancing improved heuristic drift elimination for step-and-heading based pedestrian dead-reckoning systems

Area of Science:

• Indoor positioning systems
• Healthcare technology
• Sensor fusion

Background:

• Location-based services (LBS) enhance patient care and healthcare efficiency.
• Pedestrian Dead Reckoning (PDR) using inertial sensors is a cost-effective indoor positioning solution.
• PDR systems suffer from drift errors, particularly heading drift, limiting accuracy.

Purpose of the Study:

• To enhance the improved heuristic drift elimination (iHDE) method for Step-and-Heading (SHS) based PDR systems.
• To evaluate the performance of the enhanced iHDE method with wrist-worn inertial sensors.
• To demonstrate the effectiveness of iHDE in reducing heading drift without compromising PDR accuracy.

Main Methods:

• Implementation of the enhanced iHDE method within an SHS-based PDR framework.
• Utilizing building's dominant directions to correct heading drift.
• Testing the system with both synthetically generated and real-world sensor data.
• Employing wrist-worn inertial sensors for practical application.

Main Results:

• The enhanced iHDE method successfully reduces heading drift in SHS-based PDR systems.
• The method maintains its heading drift reduction capability when implemented with wrist-worn sensors.
• Performance evaluation on diverse datasets confirmed the method's efficacy.

Conclusions:

• The enhanced iHDE method is a viable solution for mitigating heading drift in PDR systems.
• This approach allows for flexible sensor placement, including wrist-worn devices.
• The findings support the integration of advanced PDR techniques into LBS for improved healthcare applications.