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A Novel Arithmetic Optimization PDR Algorithm for Smartphones.

Mingze Zhang1, Aigong Xu1

  • 1School of Geomatics, Liaoning Technical University, Fuxin 123000, China.

Sensors (Basel, Switzerland)
|December 11, 2025
PubMed
Summary
This summary is machine-generated.

A novel Arithmetic Optimization Algorithm for Pedestrian Dead Reckoning (PDR) efficiently optimizes system parameters for smartphones. This AO-PDR algorithm achieves accurate pedestrian positioning with a mean error of 0.2893 m.

Keywords:
AO-PDRfitness functionheading correction mechanismlocation-based serviceoptimal system parameterssmartphones

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Area of Science:

  • Computer Science
  • Navigation Systems
  • Algorithm Optimization

Background:

  • Pedestrian Dead Reckoning (PDR) systems require accurate parameter settings for reliable performance.
  • Existing PDR algorithms face challenges in parameter optimization, impacting positioning accuracy.

Purpose of the Study:

  • To propose a novel Arithmetic Optimization PDR (AO-PDR) algorithm for smartphones.
  • To optimize PDR system parameters for enhanced accuracy and efficiency.

Main Methods:

  • Developed an AO-PDR algorithm utilizing the Arithmetic Optimization Algorithm (AOA).
  • Established a fitness function based on positioning error, step deviation, and step length deviation.
  • Applied AOA to search for optimal parameters for step detection, length estimation, and heading correction.

Main Results:

  • The AO-PDR algorithm efficiently and accurately obtained optimal system parameters.
  • Achieved a mean optimal fitness of 1.352 with a mean running time of 164.85 seconds.
  • Demonstrated high adaptability, efficiency, and stability across different users and devices, with a mean positioning error of 0.2893 m.

Conclusions:

  • The AO-PDR algorithm effectively optimizes PDR parameters, leading to improved pedestrian positioning accuracy.
  • The proposed method meets the accuracy requirements for pedestrian location-based services.
  • AO-PDR offers a robust and efficient solution for smartphone-based pedestrian navigation.