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Sensors 2016, 16(9), 1423; doi:10.3390/s16091423

Step-Detection and Adaptive Step-Length Estimation for Pedestrian Dead-Reckoning at Various Walking Speeds Using a Smartphone

School of Electrical Engineering, Kookmin University, 861-1 Jeongnung-dong, Seongbuk-gu, Seoul 136-702, Korea
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Academic Editor: Angelo Maria Sabatini
Received: 12 April 2016 / Revised: 25 August 2016 / Accepted: 29 August 2016 / Published: 2 September 2016
(This article belongs to the Section Physical Sensors)
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Abstract

We propose a walking distance estimation method based on an adaptive step-length estimator at various walking speeds using a smartphone. First, we apply a fast Fourier transform (FFT)-based smoother on the acceleration data collected by the smartphone to remove the interference signals. Then, we analyze these data using a set of step-detection rules in order to detect walking steps. Using an adaptive estimator, which is based on a model of average step speed, we accurately obtain the walking step length. To evaluate the accuracy of the proposed method, we examine the distance estimation for four different distances and three speed levels. The experimental results show that the proposed method significantly outperforms conventional estimation methods in terms of accuracy. View Full-Text
Keywords: Weinberg method; PDR; step length; step-detection; FFT filter Weinberg method; PDR; step length; step-detection; FFT filter
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Ho, N.-H.; Truong, P.H.; Jeong, G.-M. Step-Detection and Adaptive Step-Length Estimation for Pedestrian Dead-Reckoning at Various Walking Speeds Using a Smartphone. Sensors 2016, 16, 1423.

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