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Simulation of Human-induced Vibrations Based on the Characterized In-field Pedestrian Behavior
Published on: April 13, 2016
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Indoor Pedestrian Self-Positioning Based on Image Acoustic Source Impulse Using a Sensor-Rich Smartphone.
Xiyu Song1, Mei Wang2, Hongbing Qiu3
1Ministry of Education Key Laboratory of Cognitive Radio and Information Processing, GuiLin University of Electronic Technology, Guilin 541004, China. songxiyu@guet.edu.cn.
Sensors (Basel, Switzerland)
|November 30, 2018
Summary
This study introduces a novel indoor positioning system combining acoustic and pedestrian dead reckoning (PDR) methods. The new approach significantly reduces positioning errors, enhancing accuracy for smartphone-based pedestrian tracking.
Area of Science:
- Ubiquitous Computing
- Sensor Networks
- Acoustic Signal Processing
Background:
- Pedestrian dead reckoning (PDR) using smartphones is common for indoor tracking.
- PDR suffers from cumulative errors, limiting its accuracy.
- Existing methods often require specialized infrastructure.
Purpose of the Study:
- To develop a low-cost, infrastructure-free indoor positioning method.
- To improve the accuracy of pedestrian tracking using smartphones.
- To mitigate the cumulative error inherent in PDR.
Main Methods:
- Combining infrastructure-free indoor acoustic self-positioning with PDR.
- Verifying PDR results using acoustic constraints between sound and image sources.
- Determining first-order echo delay measurements for mobile user positioning.
Main Results:
- Achieved a continuous self-positioning median error of 0.19 m.
- Attained an error probability below 0.12 m for 54.46% of measurements.
- Demonstrated effective elimination of PDR cumulative errors.
Conclusions:
- The proposed hybrid acoustic-PDR method offers high accuracy for indoor pedestrian tracking.
- The system is robust against environmental disturbances.
- Smartphone-based acoustic positioning presents a viable alternative for indoor navigation.
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