A Novel Pedestrian Dead Reckoning Algorithm for Multi-Mode Recognition Based on Smartphones

Limin Xu,Zhengchun Wang,Jianye Liu,Yiming Ding,Zhi Xiong

doi:10.3390/rs11030294

Abstract

With the rapid development of smartphone technology, pedestrian navigation based on built-in inertial sensors in smartphones shows great application prospects. Currently, most smartphone-based pedestrian dead reckoning (PDR) algorithms normally require a user to hold the phone in a fixed mode and, thus, need to correct the gyroscope heading with inputs from other sensors, which restricts the viability of pedestrian navigation significantly. In this paper, in order to improve the accuracy of the traditional step detection and step length estimation method for different users, a state transition-based step detection method and a step length estimation method using a neural network are proposed. In order to decrease the heading errors and inertial sensor errors in multi-mode system, a multi-mode intelligent recognition method based on a neural network was constructed. On this basis, we propose a heading correction method based on zero angular velocity and an overall correction method based on lateral velocity limitation (LV). Experimental results show that the maximum positioning errors obtained by the proposed algorithm are about 0.9% of the total path length. The proposed novel PDR algorithm dramatically enhances the user experience and, thus, has high value in real applications.

Highlights

With the development of society, location-based service became part of people’s lives
In order to verify the proposed novel pedestrian dead reckoning (PDR) algorithms (IM_PDR+zero angular velocity (ZA)+LV), three methods were used as control groups as follows: (1) MTS-ZUPT/GA: PDR algorithm based on Middle Time Simulated-Zero Velocity Update and Gravity Assisted methods proposed in Reference [24]
To demonstrate the effectiveness of the heading correction method based on zero angular velocity and the overall correction method based on lateral velocity limitation, we performed two types of experiments

Summary

Introduction

With the development of society, location-based service became part of people’s lives. Pedestrian indoor navigation technology is critical to ensure the success of location-based services. The first type of method is based on wireless technologies, e.g., WiFi [3,4,5], ultra-wideband (UWB) [6,7], visual sensors [8], radio frequency identification (RFID) [9], ibeacon [10], Bluetooth, and/or ZigBee, with a multi-source information fusion technique [11] to obtain pedestrian location information. For the first type of method, its location errors do not accumulate over time. These methods need a significant cost to deploy wireless devices as beacons before navigation and are infeasible for the unknown environment

Methods

Results

Discussion

Conclusion