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Chunyang Yu1,2, Naser El-Sheimy3, Haiyu Lan4

  • 1College of Automation, Haibin Engineering University, Harbin 150001, China. chunyang.yu@ucalgary.ca.

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Summary
This summary is machine-generated.

This study introduces a low-cost indoor navigation system using smartphone sensors and map data. The method enhances accuracy and speed for accessible individual and group positioning.

Keywords:
MEMS sensorsauxiliary particle filtercascade structure algorithmindoor pedestrian navigationmap aidingmap informationmap matching

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Area of Science:

  • Robotics and Autonomous Systems
  • Geomatics Engineering
  • Sensor Fusion

Background:

  • Indoor navigation systems often rely on complex infrastructure, limiting accessibility and increasing costs.
  • Existing methods using microelectromechanical systems (MEMS) sensors can suffer from cumulative errors and computational demands.

Purpose of the Study:

  • To develop a non-infrastructure-based, low-cost indoor navigation solution.
  • To improve the computational efficiency and accuracy of indoor positioning systems.
  • To create an accessible navigation method for individual and group users.

Main Methods:

  • Integration of smartphone MEMS sensors with indoor map information.
  • Application of an Auxiliary Particle Filter (APF) for navigation.
  • Design of a cascade Kalman Particle Filter algorithm to reduce computational load.
  • Utilizing zero velocity updates and non-holonomic constraints within the Kalman filter.
  • Implementing map-matching and map-aiding techniques in the particle filter.

Main Results:

  • The proposed method offers a non-infrastructure-based and low-cost approach to indoor navigation.
  • A cascade Kalman Particle Filter algorithm enhances estimation speed and reduces computational burden.
  • The integration of map-matching and map-aiding in the particle filter constrains navigation solutions effectively.
  • Experimental validation confirms the availability and accuracy of the algorithm in practical scenarios.

Conclusions:

  • The developed indoor navigation system is accurate, efficient, and cost-effective.
  • The method simplifies indoor positioning, making it suitable for diverse user groups.
  • This research contributes a practical solution for accessible and reliable indoor navigation.