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Related Experiment Video

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Microfluidic Platform with Multiplexed Electronic Detection for Spatial Tracking of Particles

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An Algorithm with Iteration Uncertainty Eliminate Based on Geomagnetic Fingerprint under Mobile Edge Computing for

Jie Li¹, Liming Sun¹, Dongpeng Liu²

¹School of Computer Science and Engineering, Northeastern University, Shenyang 110169, China.

Sensors (Basel, Switzerland)

|December 11, 2022

Summary

This study introduces GeoLoc, an indoor localization algorithm using sensor fusion to improve accuracy. GeoLoc offers precise and stable positioning for indoor location-based services without external infrastructure.

Keywords:

Kalman filter PDR edge computing indoor localization magnetic fields multisensor fusion sensors

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Area of Science:

Sensor Fusion
Indoor Localization
Edge Computing

Background:

Traditional indoor localization methods like WLAN and GPS lack sufficient precision.
Complex location calculations on edge devices lead to resource constraints and delays.

Purpose of the Study:

To present GeoLoc, a novel indoor localization algorithm utilizing sensor fusion.
To enable high-precision, stable indoor positioning on edge devices with limited resources.
To overcome limitations of existing infrastructure-dependent and sensor-based localization techniques.

Main Methods:

Fusion of acceleration, angular rate, and magnetic field sensor data.
Iterative orientation updating and position selection to reduce uncertainty.
Magnetic map building and value matching for enhanced accuracy.
Trajectory filtering from a path set for smooth positioning.

Main Results:

Achieved positioning accuracy of less than 2.5 meters in indoor environments.
Demonstrated stable and reliable positioning results.
Successfully reduced orientation uncertainty through iterative data fusion.

Conclusions:

GeoLoc provides a robust solution for indoor localization challenges.
The algorithm is suitable for deployment on edge devices, addressing computational limitations.
GeoLoc offers infrastructure-free localization, overcoming geomagnetic fingerprint non-uniqueness and sensor deviation issues.