Smartphone-Based 3D Indoor Pedestrian Positioning through Multi-Modal Data Fusion.

Hongyu Zhao,Jianjun Wang,Wanli Cheng,Ning Yang,Sen Qiu,Zhelong Wang

doi:10.3390/s19204554

Abstract

Combining research areas of biomechanics and pedestrian dead reckoning (PDR) provides a very promising way for pedestrian positioning in environments where Global Positioning System (GPS) signals are degraded or unavailable. In recent years, the PDR systems based on a smartphone’s built-in inertial sensors have attracted much attention in such environments. However, smartphone-based PDR systems are facing various challenges, especially the heading drift, which leads to the phenomenon of estimated walking path passing through walls. In this paper, the 2D PDR system is implemented by using a pocket-worn smartphone, and then enhanced by introducing a map-matching algorithm that employs a particle filter to prevent the wall-crossing problem. In addition, to extend the PDR system for 3D applications, the smartphone’s built-in barometer is used to measure the pressure variation associated to the pedestrian’s vertical displacement. Experimental results show that the map-matching algorithm based on a particle filter can effectively solve the wall-crossing problem and improve the accuracy of indoor PDR. By fusing the barometer readings, the vertical displacement can be calculated to derive the floor transition information. Despite the inherent sensor noises and complex pedestrian movements, smartphone-based 3D pedestrian positioning systems have considerable potential for indoor location-based services (LBS).

Highlights

Nowadays, almost everyone has their own smartphone, as people’s daily life cannot be separated from the convenience provided by some functions of smartphones [1]
X (Apple Inc., Cupertino, CA, USA), which has the dimensions of 143.6 mm × 70.9 mm × 7.7 mm and a weight of 174 g, and which is equipped with all the necessary sensors including three-axis accelerometer, three-axis gyroscope, three-axis magnetometer, and barometer
A 3D indoor pedestrian positioning algorithm is proposed based on a pocket-worn smartphone, by fusing the available indoor map content with the sensed walking data from the smartphone’s built-in sensors, including accelerometer, gyroscope, magnetometer, and barometer

Summary

Introduction

Almost everyone has their own smartphone, as people’s daily life cannot be separated from the convenience provided by some functions of smartphones [1]. Most smartphones have a wealth of sensors or systems built into them, such as the Global Positioning System (GPS), Wi-Fi, photoreceptor, microphone, magnetometer, barometer, inertial sensors (i.e., gyroscopes and accelerometers), etc. Localization and navigation via a global navigation satellite system (GNSS) has become an important part in smartphones daily use. GNSS can provide accurate location information in outdoor environments, there are considerable challenges when it is used in indoor or indoor-like environments, such as inside buildings, tunnels or caves, as well as in urban canyons, deep canopies or dense forests [2]. As people spend most of Sensors 2019, 19, 4554; doi:10.3390/s19204554 www.mdpi.com/journal/sensors

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