IRT-SD-SLE: An Improved Real-time Step Detection and Step Length
Estimation using Smartphone Accelerometer
Abstract
Smartphone sensor-based pedestrian dead reckoning (PDR) systems provide
a viable solution to the problem of localization in an
infrastructure-less area. Step detection (SD) and step length estimation
(SLE), being two fundamental operations of the PDR based localization
technique, have drawn many researchers’ attention in the recent time.
Most of the existing SD and SLE methods proposed over the years,
however, provide either server- or cloud-based solution that consume
additional network bandwidth and suffer from increased transmission
delay. Moreover, nonavailability of the inertial sensors like gyroscope,
magnetometers etc. at every smartphone makes majority of the existing
SLE methods less applicable to such devices. To address the above-said
issues, in this paper we focus on devising an improved SLE method that
would detect the pedestrian’s steps and subsequently estimate the step
length in real-time by processing the accelerometer data at the device
itself. Our proposed method transforms the measured acceleration values
along the earth coordinate system and also applies sliding window
meaning to mitigate the negative effects of the smartphone’s orientation
and gravitational bias on the accuracy of SD and SLE. The performances
of our proposed method are evaluated in terms of accuracy for five
different users by taking the device in two different postures (handheld
and trouser pocket) under two different walking modes (normal and fast)
to demonstrate its efficacy. Moreover, our proposed method also obtains
more than 88% accuracy (median) for all participants when the device is
placed in trouser pocket under two different walking modes.